United States Office of EPA/600/4-91/026
Environmental Protection Research and Development October 1991
Agency Washington, DC 20460
&EPA | Example Environmental
Assessment Report for
Estuaries
Environmental Monitoring and
Assessment Program
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EPA/600/4-91/026
EXAMPLE ENVIRONMENTAL
ASSESSMENT REPORT FOR
ESTUARIES
by
Jeffrey B. Frithsen
Versar, Inc.
Columbia, MD 21045
Jeroen Gerritsen
Versar, Inc.
Columbia, MD 21045
Gary Saul
FIN Associates, Ltd.
Austin, TX 78741
Project Officers
Linda Kirkland (Contract Nos. 68-DO-0093
and 68-09-0094)
Office of Modeling, Monitoring Systems and
Quality Assurance
Washington, DC 20460
Seymour Hochheiser (Contract No. 68-02-4444)
Atmospheric Research and Exposure
Assessment Laboratory
Research Triangle Park, NC 27711
Mary C. Fabrizio
ManTech EnvironmentalTechology, Inc.
Research Triangle Park, NC 27709
A. Frederick Holland
Versar, Inc.
Columbia, MD 21045
Stephen B. Weisberg
Versar, Inc.
Columbia, MD 21045
Tom Murray (Contract No. 68-.D9-0166)
Office of Toxic Substances
Washington, DC 20460
Marijon Bufalini (Contract No.
68-D-00-106)
Atmospheric Research and Exposure
Assessment Laboratory
Research Triangle Park, NC 27711
ENVIRONMENTAL MONITORING AND ASSESSMENT PROGRAM
OFFICE OF RESEARCH AND DEVELOPMENT
ATMOSPHERIC RESEARCH AND EXPOSURE ASSESSMENT LABORATORY
U.S. ENVIRONMENTAL PROTECTION AGENCY
RESEARCH TRIANGLE PARK, NC 27711
Printed on Recycled Paper
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The suggested citation for this report is:
Frithsen, J.B., M.C. Fabrizio, J. Gerritsen, A.F. Holland, G.E. Saul, and S.B.
Weisberg, 1990. Example Environmental Assessment Report for Estuaries.
EPA/600/05-91/XXX. U.S. Environmental Protection Agency Atmospheric
Research and Exposure Assessment Laboratory, Research Triangle Park, NC.
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PREFACE
A year ago, EMAP scientists assembled to
discuss the value of assessment reports and to
produce an example of such a report. The exam-
ple was intended to demonstrate to EMAP clients
the type of information provided by the monitor-
ing program and the interpretation of that infor-
mation in a policy-relevant context. This example
report for an estuarine province is the result of
those efforts. The purpose of this preface is to
examine some of the issues and questions that
emerged during this initiative, especially those
which require further consideration by program
scientists. Briefly, the three issues are: "environ-
mental" versus "ecological" assessments, use of
nominal-subnominal designations for exposure
indicators, and the construction of ecological
indices. The approaches demonstrated in this
report represent a possible strategy; however,
other possibilities merit consideration.
Environmental Versus Ecological Assessments
The question of the appropriate name for
assessment reports arose because this is the first
report concerning "EMAP data" (note that data
for the example report were simulated). Two
names are under consideration: an environmental
assessment or an ecological assessment. Al-
though this may appear to be a simple semantics
issue, it is not. The program is the Environmental
Monitoring and Assessment Program and its
name reflects the desire to monitor ecological
indicators that can be used to make statements
about attributes of the environment valued by
society (e.g., biodiversity, sustainability of re-
sources, and aesthetics). These attributes,
termed "assessment endpoints" in EMAP, guide
the selection of ecological indicators actually
measured by the field monitoring program.
Because EMAP indicators are selected to reflect
attributes valued by society, the reports are
"environmental assessments." This designation
is consistent with use of this term by other EPA
programs, where the term "environmental" often
refers to human health issues. Although EMAP
assessments are not directly concerned with
human health, the focus tends to be human use
of the environment and societal values associated
with ecological resources.
In contrast, some scientists have argued that
assessment reports should be termed "ecological
assessments" to reflect EMAP's unique approach.
EMAP monitoring focuses on measures of the
condition of organisms, populations, communi-
ties, or ecosystems (response indicators); EMAP
assessments present interpretations of these
measures and make statements concerning the
condition of our nation's resources. Analogous to
retrospective risk assessments, this approach has
been described as a "top-down" (or inductive)
approach because the program will identify
biological communities and populations character-
ized by subnominal (unacceptable) condition and
then associate observed condition with various
indicators of exposure to physical, chemical, or
biological stress (exposure indicators). These
associations, in turn, are examined in light of
indicators of stress (pollutant discharges, efflu-
ents, etc.). Traditionally, monitoring programs
have focused on measuring sources of physical
or chemical stress such as emissions, discharges,
and effluents. The use of the term "ecological
assessment" emphasizes the importance of
measuring resource responses rather than pollut-
ant discharges.
The current document is titled an "environ-
mental assessment" for reasons stated previously
and because assessment reports will likely con-
tain information on human use, and indirectly,
human health. An example to consider is the
assessment of shellfish populations in estuarine
environments with respect to condition of the
population (biomass, density, etc.). Although the
population may be judged in nominal or accept-
able condition, these same shellfish beds may be
closed to commercial and recreational harvesting
due to exposures to improperly treated sewage.
Human use of this resource is diminished (due to
possible human health issues related to consump-
tion of contaminated shellfish) and it may be
desirable to report such cases.
Although the designation of assessment
reports as either "ecological" or "environmental"
is not, in itself, a major issue, it reflects program-
matic considerations of EMAP's scope and the
emphasis of future assessments which invite
further thought.
in
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Exposure Indicators and Nominal-Subnominal
Designations
in this example report, the authors present
and summarize information on exposure indica-
tors using nominal-subnominal designations. The
EMAP indicator strategy clearly identifies these
designations for response indicators only. Nomi-
nal conditions exist where ecological resources
are acceptable relative to a measurement or
assessment endpoint. Those resources that do
not meet these conditions are characterized as
having subnominal conditions. Thus, these terms
are used to describe the condition of the bio-
sphere. The use of nominal-subnominal to differ-
entiate between two levels of an exposure indica-
tor implies knowledge of the biotic effects of a
particular exposure indicator. For example,
subnominal concentrations of mercury in estua-
rine sediments implies that these concentrations
are associated with deleterious effects on the
biotic component (e.g., benthic communities).
These relationships are simply not known for
many of the indicators of exposure and response
measured by EMAP. Dissolved oxygen in the
water column is, however, a noteworthy excep-
tion. Concentrations below 2 mg 02/l are gener-
ally considered lethal to most marine organisms;
similarly, concentration between 2 and 5 mg 02/l
adversely affect some aquatic organisms. The
example report uses the term subnominal to refer
to dissolved oxygen concentrations below 2 mg/l
(marginal [2-5 mg/l], and nominal [above 5 mg/l]
categories are also defined). Ignoring this knowl-
edge about the general relationship between
dissolved oxygen concentrations and stress in
marine organisms would detract from the power
of the assessment and place arbitrary limitations
on EMAP's ability to share important information
about estuarine condition.
In addition, the term subnominal was used to
designate fish tissues with contaminant concen-
trations above a certain level, depending on the
contaminant. Here, subnominal is in reference to
FDA action limits currently available for some
contaminants. The authors reasoned that in the
future, many more contaminants would have FDA
action limits and that action limits would be
available for sediment contaminants as well. The
relationship between action limits for fish tissue
(or sediment) contaminants and condition of
organisms, populations, or communities is not
known. When these relationships become well
known, they may be treated in a manner similar
to the dissolved oxygen-biotic response relation-
ships.
Perhaps the use of nominal-subnominal
designations for exposure indicators is unwarrant-
ed. Ideally, these terms should be reserved for
descriptions of ecological condition (response
indicators). However, the analysis of exposure
indicators requires the use of categories (above '
or below a particular concentration) in order to
make interpretations concerning the relationship
between condition of a resource and environmen-
tal exposure. By categorizing exposure indicator
data, EMAP can enhance analysis and facilitate
interpretation of multidimensional monitoring
data. For this reason, the approach itself is
recommended -- that is, use of categories of
exposure levels, but the names of those catego-
ries should be descriptive ones such as "below 2
mg/l" or "above 5 ppm," rather than value-ori-
ented ones such as subnominal or nominal.
Index Construction
Lastly, the construction of an index for
estuarine condition is a challenge put forth by
this example report. Indices are attractive be-
cause they offer simple summaries and readily
communicate information about environmental
values - the principal reason for preparing assess-
ment reports. The public is familiar with indices
such as the Index of Leading Economic Indica-
tors, an index used to assess the state of our
nation's overall economy. In recent years, fish-
ery biologists have used the Index of Biotic
Integrity I1B1) to examine changes in stream fish
communities. The IB) summarizes information on
species diversity (e.g., number of sucker species)
and community composition (e.g., percent of
individuals as top carnivores) and is used to
assess the quality of streams and rivers for
fishes. The Index of Leading Economic Indicators
and the IB! are examples of indices developed
from measures of similar attributes (economic
factors and fish, respectively). Applying the
concept of indices to ecological communities
requires an understanding of the functional
relationship of vastly different measures -- for
example, benthic biomass, fish tissue contami-
nants, and aesthetic aspects of estuarine environ-
ments.
IV
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The suggestion that such an index may be
developed is intriguing and points to at least
three directions for future research. First should
there be multiple indices for describing overall
estuarine condition, each one keyed to a single
value such as biodiversity or productivity?
Second, what are the elements (indicators)
necessary for compilation of such an index?
And, third, what are the appropriate social sci-
ence methodologies required in order to consider
aesthetic indicators? The rigorous treatment of
ecological data with respect to biotic integrity
(e.g. benthic communities, fish tissue contami-
nants), must be paralleled by equally rigorous
efforts to assign meaning to various aesthetic
indicators or indicators of human use of estuar-
ies. For example, how does one quantify an
acceptable amount of trash in estuarine systems?
These three questions invite further discussions
of the role EMAP will play in communicating
ecological information.
This example report for an estuarine province
represents a first attempt to illustrate, and there-
by define, EMAP assessment reports. It is highly
unlikely that future assessments will closely
resemble this example. However, this report has
contributed a wealth of information to the
DC
Gary J. FoleV^§*reitor
Atmospheric ResWrch and Exposure
Assessment Laboratory
Research Triangle Park, NC
" ~Pa FMAPCENTFR
-.' riat'on services
,ViO-75
" "" ,'IC 27711
process of defining assessments. Perhaps it has
generated more questions than it answered. But
knowing how to ask the right question is the first
step in finding a solution.
This example report has identified ways that
EMAP scientists and EMAP clients can refine and
direct the program so that relevant ecological
information is communicated in an effective
manner. We are currently developing an example
integrated assessment that addresses overall
ecological condition of entire biogeographic
regions. Actual data from our Near-Coastal and
Forest Demonstration Projects are presently being
interpreted. Not only are we learning how to
improve monitoring, but also how to address
assessment needs and goals. These efforts,
coupled with significant progress throughout
EMAP, will continue to improve the quality of our
environmental assessments.
For additional information regarding EMAP's
assessment efforts, please contact Daniel A.
Vallero, Technical Coordinator for Integration and
Assessment, Atmospheric Research and Exposure
Assessment Laboratory, MD-75, U. S. Environ-
mental Protection Agency, Research Triangle
Park, N. C. 27711.
Frederick W. Kutz, Acting Direct
Environmental Monitoring and
Assessment Program
Washington, DC
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DISCLAIMER
The information in this document has been tract number 68-D9-0094 to FTN Asso-ciates,
funded wholly or in part by the U.S. Environmen- Ltd. It has been subjected to the Agency's peer
tal Protection Agency (Environmental Monitoring and administrative review, and it has been ap-
and Assessment Program, Office of Research and proved for publication as an EPA document.
Development) under contract numbers 68-D9- Mention of trade names or commercial products
0166 and 68-DO-0093 to Versar, Inc., contract does not constitute endorsement or recommenda-
numbers 68-02-4444 and 68-DO-0106 to Man- tion for use.
Tech Environmental Technology, Inc., and con-
NOTICE
The data used to create the example assessment sions, and interpretations are based on synthetic
report in Section 2 are fictional. They do not data; therefore, text, tables, and figures should
represent actual ecological status or trends for not be used or cited in any other document.
any region of the nation. The analyses, conclu-
VII
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ACKNOWLEDGEMENTS
This document was prepared by Versar, Inc.,
with assistance from ManTech Environmental
Technology, Inc., and FTN Associates, Ltd.
Individuals who made significant contributions to
this project were: William Baillargeon, Edward
Barrows, Don Block, and Karl Hermann (ManTech
Environmental Technology, Inc., Research Trian-
gle Park, NC), and Carol DeLisle, Michael
Gaughan, and Jingyee Kou (Versar, Inc., Colum-
bia, MD). This project greatly benefitted from
comments received from Doug Heimbuch (Coast-
al Environmental Services, Inc., Linthicum,
MD), Scott Overton (Oregon State University,
Corvallis, OR), Kent W. Thornton (FTN Associ-
ates, Ltd., Little Rock, AR), Dean Carpenter and
Luther Smith (ManTech Environmental Tech-
nology, Inc., Research Triangle Park, NC),
Woollcott Smith (Temple University, Philadelphia,
PA), and the following employees of the U.S.
Environmental Protection Agency: Tom DeMoss,
(Annapolis, MD), Kim Devonald, Tom Dixon, Rick
Linthurst (Washington, DC), Eric Hyatt, Daniel
Vallero (Research Triangle Park, NC), Bruce Jones
(Las Vegas, NV), Joel O'Connor (New York, NY)
and J. Kevin Summers (Gulf Breeze, FL).
IX
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CONTENTS
Page
PREFACE iii
NOTICE vii
ACKNOWLEDGEMENTS ix
TABLE OF CONTENTS xi
LIST OF BOXES xiii
LIST OF FIGURES xiv
LIST OF TABLES xvi
SECTION 1: FOREWORD 1-1
SECTION 2: EXAMPLE ASSESSMENT REPORT 2-1
EXECUTIVE SUMMARY 2-3
ESTUARIA 2-3
EPA REGIONS 2-4
ESTUARY CLASSES 2-4
CONCLUSIONS 2-4
INTRODUCTION 2-7
OBJECTIVES OF THIS REPORT 2-8
ESTUARIA 2-8
PROGRAM DESIGN 2-8
Indicators 2-8
Indices 2-12
Indicator Thresholds 2-12
SAMPLING AND ANALYSIS 2-14
ASSESSMENT OF ESTUARINE ECOSYSTEMS 2-17
EVALUATING SUBNOMINAL CONDITION: BIOLOGICAL COMMUNITIES 2-17
Toxic Sediments 2-18
Dissolved Oxygen 2-19
Unknown Impacts 2-20
EVALUATING SUBNOMINAL CONDITION: HUMAN USE 2-21
ASSESSMENT BY ADMINISTRATING REGION 2-22
ASSESSMENT BY RESOURCE CLASS 2-23
EFFECTIVENESS OF REGULATORY PROGRAMS 2-26
CONCLUSIONS 2-29
LITERATURE CITED 2-31
XI
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CONTENT^ (Cont'd)
Page
SECTION 3: DATA SET SIMULATION 3-1
DEVELOPMENT OF A GEOGRAPHIC MAP 3-1
INDICATOR AND INDEX SELECTION 3-2
BASE DATA SET 3-6
Contaminant Indicators 3-6
Dissolved Oxygen 3-7
Benthic Indicators and Index . 3-7
Fisheries Index 3-7
Habitat indicators 3-7
Stressor Indicators 3-7
TEMPORAL TRENDS AND ASSOCIATIONS 3-8
ASSUMPTIONS 3-11
Sampling Design 3-11
Indicator Thresholds 3-11
DETERMINATION OF STATUS 3-13
SECTION 4: LESSONS LEARNED 4-1
ASSESSMENT REPORTS AND ANNUAL STATIST8CAL SUMMARIES 4-1
ANALYTICAL APPROACHES 4-2
Use of CDFs 4-3
Index Development 4-3
Subnomina! Thresholds 4-3
Analysis 4-4
Data From Other Sources 4-4
Display of Data on Maps 4-4
APPLICATIONS OF REALISTIC DATA SETS . 4-6
CONCLUSIONS 4-7
SECTION 5: REFERENCES 5-1
XII
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UST OF BOXES
Page
2-1 EMAP Indicator Types 2-12
2-2 Statistical Confidence 2-15
2-3 Sampling Methods 2-16
XIII
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UST OF FIGURED
Pace
2-1 Percent of estuarine area in Estuaria having subnominal conditions 2"3
2-2 Percent of estuarine area in Estuaria with subnominal concentrations of lead
and DDT in sediments 2-4
2-3 Percent of estuarine area in Regions A and B with toxic sediments 2-4
2-4 Percent of estuarine area in the three classes of estuaries with subnominal
concentrations of dissolved oxygen 2-5
2-5 Political boundaries for Estuaria and Fredonia 2-9
2-6 Land use pattern for Estuaria 2-10
2-7 Relationships between EMAP indicator types 2-11
2-8 Components of estuarine indices 2-13
2-9 Percent of estuarine area in Estuaria having subnominal conditions 2-17
2-10 Percent of estuarine area with subnominal, marginal, and nominal conditions
(years 9-12) 2-17
2-11 Percent of estuarine area in Estuaria with nominal conditions 2-18
2-12 Percent of estuarine area in Estuaria with toxic sediments 2-18
2-13 Percent of estuarine area in Estuaria with subnominai concentrations of
Contamexx in sediments 2-19
2-14 Annual use in metric tons of Contamexx in Region A 2-19
2-15 Percent of estuarine area in Estuaria with subnominal concentrations of
lead and DDT in sediments 2-19
2-16 Annual atmospheric emissions of lead in Estuaria in metric tons 2-20
2-17 Annual use in metric tons of DDT in Estuaria 2-20
2-18 Percent of estuarine area in Estuaria with subnominal concentrations
of dissolved oxygen 2-20
2-19 Percent of estuarine area in Estuaria with marginal or nominal concen-
trations of dissolved oxygen 2-21
2-20 Percent of estuarine area in Estuaria with subnominal biological communities
associated with subnominal oxygen concentrations 2-21
XIV
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FIGURES (Cont'd)
Page
2-21 Percent of estuarine area in Estuaria with nominal concentrations
for all measured contaminants in fish tissues 2-21
2-22 Percent of estuarine area in Estuaria with subnominal concentrations
of Contamexx in fish tissues 2-22
2-23 Percent of estuarine area in Estuaria with subnominal concentrations
of mercury, lead, or DDT in fish tissues 2-22
2-24 Percent of area in Regions A or B with subnominal estuarine conditions 2-22
2-25 Percent of estuarine area in Regions A or B with nominal estuarine
conditions 2-23
2-26 Percent of estuarine area in Regions A or B with toxic sediments 2-23
2-27 Percent of estuarine area in Regions A or B with subnominal
concentrations of Contamexx in sediments 2-23
2-28 Distribution of areas with subnominal concentrations of Contamexx 2-24
2-29 Percent of estuarine area in Regions A or B with subnominal
concentrations of Contamexx in fish tissues 2-25
2-30 Percent of estuarine area in each resource class with subnominal
estuarine conditions 2-25
2-31 Percent of area in resource classes with subnominal oxygen concentrations 2-25
2-32 Percent of estuarine area in resource classes with toxic sediments 2-26
2-33 Percent change throughout estuaries for four land use classifications 2-26
3-1 Components of estuarine indices proposed for EMAP 3-5
3-2 Example cumulation distribution function 3-13
XV
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LIST OF TABLES
Tab8e Page
2-1 Subnominal, Marginal, and Nominal Ranges for Indicators
and Indices 2-14
2-2 Characteristics of Estuarine Classes 2-15
3-1 Construction of Simulated Data Set Base Variables 3-3
3-2 Simulated Temporal Trends 3-9
3-3 Associations Built-in to Data Set 3-12
4-1 Comparison of EMAP Annual Statistical Summaries and
Assessment Reports 4-2
XVI
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SECTION 1
FOREWORD
This nation expends considerable resources on
environmental protection and monitoring. The
costs for pollution abatement in the United States
are estimated to be about $77 billion annually,
whereas regulation and monitoring activities cost
approximately $1.5 billion (CEQ 1990). Environ-
mental monitoring by the U.S. Environmental
Protection Agency (EPA) alone costs $350 million
annually (Hunsaker and Carpenter 1990). De-
spite these expenditures, no conclusive state-
ments can be made about the cumulative effec-
tiveness of regulatory programs, the overall
condition of the nation's environmental re-
sources, or long-term trends in ecological
condition.
The need to assess the condition of the nation's
environmental resources has been emphasized by
EPA, Congress, and private environmental organi-
zations. Responding to this need, and to recom-
mendations made by the EPA Science Advisory
Board (USEPA 1988), EPA initiated the Environ-
mental Monitoring and Assessment Program
(EMAP) (USEPA 1990).
EMAP is being designed by EPA and other federal
agencies and is coordinated by EPA's Office of
Research and Development. The program repre-
sents a long-term (decades) commitment to
assess and document the condition of the
nation's ecological resources at national, regional
(e.g. EPA Regions, the Northeast), and
subregional scales.
EMAP is designed to provide answers to the
following questions (USEPA 1990):
What is the current status, extent, and
geographic distribution of the nation's
ecological resources?
What proportions of these resources are
degrading or improving, where, and at
what rate?
What are the possible reasons for ad-
verse or improving conditions?
Are adversely affected ecosystems re-
sponding as expected to control and miti-
gation programs?
EMAP will work with a broad spectrum of collab-
orators to provide information on the status and
the change in status (trends) of the nation's
ecological resources. The program will be imple-
mented in seven types of ecosystems or ecologi-
cal resources: estuaries and coastal waters,
inland surface waters, the Great Lakes, wetlands,
forests, arid lands, and agricultural lands.
Information on the condition of each resource
category will be provided in the form of statistical
summaries and environmental assessment re-
ports. Statistical summaries will be produced
annually and will provide timely dissemination of
EMAP data in the form of tabular and graphic
data summaries.
Environmental assessment reports will be issued
periodically and will integrate EMAP data with
other monitoring programs and with environ-
mental data of other types (e.g. NPDES permit
discharge reports, USGS National Water Quality
Assessment Program (NAWQA), NOAA Status
and Trends Program). Assessment .reports will
assess the extent and magnitude of pollu-
tion impacts,
report trends,
describe the relationships among indica-
tors of ecological condition, exposure, and
stress,
identify the likely causes of poor ecologi-
cal condition,
help identify emerging problems, and
evaluate the overall effectiveness of regu-
latory and control programs on regional
scales.
1-1
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As currently envisioned, assessment reports will
be completed at four Sevels of environmental
complexity. At the first level, assessments will
be completed for a particular environmental re-
source (forests, for example) within one bio-
geographic province or region. At the second
level of integration, assessments will be com-
pleted for a particular environmental resource
across multiple regions. For example an as-
sessment might be made of all east coast
estuaries by integrating information collected in
the Acadian, Virginian, Carolinian, and West
Indian Provinces. The third type of assessment
activity to be conducted by EMAP requires the
integration of information and data across
resource groups for a complete assessment of
the overall conditions within a biogeographic
province or regoin. These types of assessments
may be made for particular EPA regions and
would not only integrate and compare conditions
within multiple types of environmental resources,
but also attempt to identify how conditions and
changes in one resource affects another. A
specific assessment, for example, might address
how changes in land use in watersheds impact
the condition of surface waters and estuaries.
Assessments that require integrating information
about multiple resources across multiple
biogeographic provinces or regions are the fourth
type of assessment activity envisioned for EMAP.
These assessments will describe the conditions
of the nation's environmental resources.
The purpose of this report is to provide an exam-
ple of an environmental assessment report for the
estuaries in one biogeographic province. It is
intended to illustrate some of the types of as-
sessments and interpretations that will be possi-
ble, as well as some of the potential limitations of
the program.
In this report we did not evaluate the EMAP
sampling design or the indicators chosen by
EMAP to monitor and assess the condition of
estuaries, nor did we evaluate our ability to
detect trends that are not monotonic. These
evaluations and tests are necessary and have
begun using historical data and various modeling
and simulation techniques. Further evaluations
will be made as data from the 1990 EMAP-
Estuaries demonstration project become avail-
able.
This document is organized in five sections: 1)
this foreword, 2) the Example Environmental
Assessment Report, 3) data set simulation, 4)
lessons learned, and 5) references. The example
report is presented as an independent document
and is written as if produced after the twelfth
year of the program. We attempted to make the
example report as close as possible to an actual
resource-specific assessment. The data pre-
sented, although based upon actual data from the
east coast of the United States, are fictional and
are used for illustrative purposes only. The
section on data simulation presents an overview
of how we constructed the data set on which the
example report is based. The concluding section
in this document presents some of the most
important lessons learned in the process of
completing this example report.
The Example Environmental Assessment Report
contains only a brief overview of EMAP and the
estuarine component of EMAP. Additional infor-
mation about EMAP and about the strategic
approach taken for this assessment are given in
the data simulation section. Although some of
this information has been published previously
(Holland 1990; Hunsaker and Carpenter 1990),
many of these documents are not yet generally
available; thus, the information warrants
reiteration.
1-2
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United States Office of Research
Environmental Protection- and Development
Agency Narragansett, Rl 02882
EPA/60C/10-03 xxx
October 2003
EPA/
NOAA
Environmental Monitoring and
Assessment Program
Assessment Rei
Estuaries
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EXECUTIVE SUMMARY
Perhaps more than any other ecological system,
estuaries are subjected to increasing use by man.
Our many uses of estuaries are often conflicting.
We depend upon estuaries as a vehicle for com-
merce and transportation, as a source of food
from both commercial and recreational fisheries,
as a playground for swimming and boating, and
we look toward the estuarine environment for
aesthetic qualities. Estuaries are also a reposito-
ry for society's contaminants and wastes. These
human activities are often in conflict with the
ecological roles of estuaries and the existence of
abundant and diverse habitats and biota.
The Environmental Monitoring and Assessment
Program (EMAP) was created to monitor the
condition of the nation's ecological resources.
EMAP monitors natural resources within large
biogeographic regions. The resources include
estuaries, coastal waters, wetlands, the Gr
Lakes, inland surface waters, forests, arid lands?
and agricultural lands. The ecological condition
of estuaries in the biogeographic provmcexpf
Estuaria, the U.S. portion of Poseidon
described in this report. The report]
years of monitoring data for estuaripe pejsbyrces.
ESTUARIA
Subnominal Estuari
ditions
cumi
There has been an overall de
ronmental conditions/
Estuarine area showi;
conditions has increj
and now compris
km2) of the total
i-
ana.
le
90 (Figure 2-1)
± 2%: 10,580
Percent"N)f estuarine area in
'aria having subnominal (un-
able) conditions. Four year
ative frequency and 90%
onfidence estimates given.
Both biologic,
logical resq
ronment f
fish and she
affecte^Jn the
er, de
widespread
dition of bio-
of the envi-
fian uses^frv consumption of
swimming^ boating) were
rfegca^ted estuarine areas; howev-
siol^oica^ integrity were more
The major findingX^ssociated with the unac-
ceptable conditions within the estuaries of
Estuaria are:
etfine in the biological condition of
estua/me resources was associated with
reases in sediment toxicity; 39% of the
as with impacted biota have toxic sedi-
ments.
The presence of Contamexx, an agricultur-
al insecticide introduced twenty years
ago, was associated with most of the es-
tuarine area with toxic sediments.
Low dissolved oxygen concentrations
were associated with 16% of degraded
biotic integrity.
Another 16% of degraded biota could not
be attributed to low oxygen concentra-
tions or toxicity due to contaminants,
suggesting that other factors also con-
tributed to degradation.
Despite the general decline in estuarine condition
in Estuaria, some conditions have improved
moderately:
Total estuarine area having sediments
contaminated with lead and DDT has
decreased by 32% and 11 %, respectively
(Figure 2-2).
2-3
-------
Total estuarine area in which levels of
lead and DDT in fish tissue has decreased
by 40% and 59%, respectively.
Subnominal Sediment Concentrations
large tidal rivers (narrow estuaries larger than
260 km2), and small estuaries (estuaries smaller
than 260 km2). Findings on these estuary class-
es were:
The areal extent of (o^sdissolved oxygen
decreased markedly irKlarse tidal rrfters
(Figure 2-4). Improving
were associate*! ^(Ith--d^creasvevin/con-
ventional pollutar
9-12
Figure 2-2. Percent of estuarine area in
Estuaria with subnominal con-
centrations of lead and DDT in
sediments. Four year cumulative
frequency and 90% confidence
estimates given.
EPA REGIONS
The decline in estuarine condition is
nounced in the estuaries of northe
(EPA Administrative Region A), a pj
agricultural region where degraded
has increased more than threefold.
Toxic sediments are
of the estuarine area
2-3).
ement/concentrations of
with all of the
within Region
the food chain in
of Contamexx
ion limits in fish
nd in 21 % of this area.
ESTUARY C
Three classes of estuaries were monitored: large
estuaries (broad estuaries larger than 260 km2),
xygen prob
aries, pois
banizatior
of theie
The exte
dissolved
small 4st
increas
th
aters with low
increased in
a result of
development in
stuaries.
have the worst environ-
l condfttanVand have undergone the
mb«ti^gradatior>NOver the past 12 years.
"^ Degrad^xajeas were associated with
toxic sedir
Occurrence of Toxic Sediments
Percent of estuarine area in Re-
gions A and B with toxic sedi-
ments. Four year cumulative
frequency and 90% confidence
estimates given.
CONCLUSIONS
EMAP data suggest that use of some agricultural
chemicals and increasing urbanization are having
deleterious effects on estuaries. Based upon
these results, the following conclusions are
drawn:
The presence of contaminants, particularly
the insecticide Contamexx and its decom-
2-4
-------
position products, is strongly associated
with subnominal estuarine conditions.
Point source controls of conventional
pollutant loadings appear to have con-
tributed to improving dissolved oxygen
conditions.
Degradation of biological resources in
small estuaries appears to be associated
with changing land use (urbanization) and
increased contaminant inputs by non-
point sources.
Attempts should be made to identify
other contributing factors in those areas
with degraded resources and for which
EMAP was unable to identify apparent
environmental stresses (16% of degraded
area).
30-
25
Subnominal Oxygen Concentrations
Large Estuaries ,
O Large Tidal Rivers
rine area in the
estuaries with
centrations of
gen. Four year
frequency and 90%
estimates given.
2-5
-------
INTRODUCTION
The Environmental Monitoring and Assessment
Program (EMAP) is a comprehensive, multiagency
program designed to ^assess the condition of U.S.
ecological resources. EMAP represents a long-
term commitment to environmental monitoring to
evaluate the overall success of current pollution
abatement policies and to identify problems
before they become wide-spread or irreversible.
EMAP provides the nation with information that
can be used to develop a strategy for reducing
degradation of the environment.
EMAP is designed to provide answers to the
following questions:
What is the current status and geograph-
ical extent of the nation's ecological re-
sources?
What resources have changed, where,
and at what rate?
To what levels of stress or pollution ar
the resources exposed in each region?
What are the possible reasons
ing or improving conditions?
What resources are at cur
risk?
Are affected resour
control and regulatory programs?
EMAP monitoring
initiated in 1990
Protection Agen
Atmospheric Adrril
assessment will
estuarine resources^
offshore waws-taitjejv
produces i^Oqrce-speci
jre
to
rpret
Environmental
nal Oceanic and
AA). This EMAP
condition of
luence with
id-of-tide. EMAP also
ssments of inland
their
surface waie<$>vwetlands,^the Great Lakes,
forests^arid laOTS^ndagroecosystems. EMAP
is spe^^hsaJlN/design^Mo assess changes in
ecologicaNx>n<{jtion over large biogeographical
regions (e.g^fi^hw^/a, the Virginian Province, the
Coastal and estuarine ecosystems are among the
most productive ecological systems and have
significant social, aesthetic, and economic value.
Estuaries provide critical feQtnq, spawning, and
nursery habitat for many
recreationally importaru^jsh, she
mammals (4,7}. More\,than
cial and recreational Ian
are taken from these systi
$7 billion is spjenTT
"22"'coastal
depend o
resource
s with
recreation in
resort economic
surrounding na\u
nation's pojtalatr
miles)
adjacent/to the
indy/triativdevelop'
d
hd
er-
ellfish
Ir/attditio'n, over
outdoor marine
, and many
e Sedition of the
fiver 75% of the
0 kilometers (50
ment, and lands
ters~~are among the most
Gulf of Mexico),
decades) in each of
>ver long time periods (e.g.,
these resource categories.
laps more-
-------
OBJECTIVES OF THIS REPORT
PROGRAM DESIGN
This report summarizes and evaluates the condi-
tion of the estuarine resources within the prov-
ince of Estuaria. Using data from the first 12
years of EMAP and other monitoring programs,
this report addresses four EMAP questions:
What is the condition of estuarine re-
sources within Estuarial
Have estuarine conditions changed over
the past 12 years and if so, to what ex-
tent?
What are the possible reasons for chang-
ing conditions?
Are adversely affected ecological re-
sources responding as expected to con-
trol and mitigation programs?
The reader is referred to other publications for
specific details concerning the general sampling
design of EMAP (8) and its estuarine componei;
(16-19) and to the preceding annual statistical"
summaries for the estuaries within Estuaria.
ESTUARIA
The geopolitical region and biogeogVaphii
ince of Estuaria is located on Poseidon Island,
proximately 200 nautical miles
in the Great Ocean. Estuaria^ (Figure
prises the western portion of Uhe island;tis
\ \ \ \
mainly agricultural in the north Wid forested ip
the south. The easterryp^ttons^ihe islapti is
foreign territory, part o/Ff^dn^\ah^i^ar\d_jlr\d
sparsely populated (Fjgurt 2-6) J Major population
centers are in the a(^ctj4wi^|yanX'nc'ustr'al nortn
and northwest and\ ir» thex«milhwest. The cli-
mate is warm and tehnperate thrmtghout most of
the island.
similar
island in
Estuaria is co
region
the so
iol estuarirtey fauna are
coast, placing the
aphic province.
administrative
6 north and Region B in
Indicators
It is not possible to monitor all environmental
resources of concern to theQtotjon. Therefore,
selected parameters which hav
be key indicators of ovefallenvironf
are measured by EMAFMo^^«*senvThaiTrhental
condition. These indica^s^afeqwirjm
valued by society, applicaDte\a/ros7v>-cange of
habitats and geo^raBKhr distances, and clearly
related to ecoloaioal condition^ TneJour types of
indicators usedlby EMAP arete&poXs«, exposure,
habitat, and str&ssqr (see Box\2\1).
's to use re~
the overall condition
dicators are used to
and identify possible
Changes in response
The EM/
sponse/ir
of a yregfbtL Expost
defim/polHiMnt exposurt
re^Sjons for potj^bondition.
exposure varia^ble^ over time are compared to
stressors to identify possible causes
>njtf tWe stressnrs. Habitat indicators are used
tr>jfue?pret va/ia^ons in response and exposure
physical attributes of the envi-
relationships among the types of
are summarized in Figure 2-1.
us on environmental condition, rather
than^on pollutant sources or ambient concentra-
Jions, reflects the unique goals of EMAP. Com-
Jiance monitoring involves identifying individual
polluters with a high degree of confidence, which
focuses attention on polluting activities and
pollutant concentrations that can be linked
unequivocally to individual sources. Information
provided by EMAP compliments compliance moni-
toring activities by assessing the overall cumula-
tive effectiveness of environmental regulations
for protecting environmental resources. New
pollutants, synergistic and antagonistic effects,
and imperfect knowledge of cause and effect
relationships in complex ecosystems makes the
biological focus essential. EMAP provides infor-
mation to help identify emerging problems and
regional resources most in need of research,
assessment, or remediation resources.
2-8
-------
POL ITICAL BOUNDARIES
ro
i
CD
Figure 2-5. Political boundaries for Estuaria and Fedonia
-------
LAND USE/LAND COVER
U r b o n
Re s i den t i o I
Agriculture
Forest
ro
O
I
Figure 2-6. Land use pattern for Estuaria
-------
Response Indicators
Habitat Indicators
Benthic Abundance
Benthic Biomass
Benthic Species Diversity
Fish Tissue Contaminants
Water Depth
Salinity
SedimenL_Char
DisspTved Oxygen
Contaminants
Sediment Toxicity
Deposition
EPA, 1990 EMAP Near Coastal Program Plan
.2-7. Relationships between EMAP indicators
2-11
-------
Indices
EMAP uses an integrated approach to make
statements concerning the condition of envi-
ronmental resources. Indices, which are mathe-
matical aggregations of response indicators, have
been developed to integrate information concern-
ing the status and trends in the condition of
environmental resources (Figure 2-8). Indices are
used to relate EMAP data directly to both the
integrity of biological resources, and quality of
the environment for human use.
The concept of balanced indigenous populations
introduced in the Clean Water Act requires the
presence of native species whose populations are
persistent over decades. This implies that spe-
cies composition is a subset of possible native
species, that the organisms are abundant enough
to maintain a population, and that the individuals
(and the population) are reasonably healthy.
The desired human uses supported by estuaries
are swimming, fishing, boating, and aesthetic
appreciation. Society values water that has
floating algal mats, trash or noxious odors,
relatively clear, safe to swim in, and supports
finfish and shellfish populations that are
eat.
Indicator Thresholds
C
Criteria established for indicators__pf biolog
response allow resources in/tjaod-oj^ciesirable
condition to be differentiate^ from thosexjr^ooor
or undesirable condition, fp \EMAP, the\r\>re
general terms nominal and
to refer to desirable a
respectively. No
healthy estuarine
species whose p
time or are desirable to
uncontaminated fisi
dissolved o
support noj
conditions*-^
d
s,
ent
ited by native
persistent over
e.g., diverse and
ommunities,
ntrationsufficient to
ations). Subnominal
$ sent degraed and undesirable
Box 2-1
EMAP Indicator Types
Response Indic
A measure of
the condition oVa^fe^ource at
organism, populatiorvcocimunij
or ecosys
(e.g., ben'
biomass).
^ \V/
ivironmental
jvide evi-
sncfe or magni-
)nke indicator's
:al, chemical,
orTxpliBgicW-sic»*s'(e.g., dissolved
oxygehs/bsncentrations or sedi-
ta>Jndicator: Physical attri-
butestrwrcmay influence the way
organisms, populations, and com-
mi/nhies respond to stresses or
jrbations (e.g., salinity or
'sptiiment type).
Stressor Information: Natural
processes, environmental hazards,
or management activities that
change exposure or habitat.
status (e.g., rfe
nativt
nated
levels of
indigenous pot
diversity^and abundance of
communities, contami-
fish,^9r"5taellfish, or insufficient
oxygen to support balanced
ns).
Although it is relatively easy to differentiate
between tra extremes of good (nominal) and
poor (subnominal) condition, it is not always easy
to designate the value at which the transition
from nominal to subnominal occurs. The term
marginal is used to classify conditions that are
not clearly nominal or subnominal. For example,
dissolved oxygen concentrations above 5 ppm
are generally accepted as nominal, and concen-
trations below 2 ppm are generally accepted as
being subnominal; dissolved oxygen concentra-
tions between 2 and 5 ppm are stressful to some
aquatic organisms, but not to all. This intermedi-
ate range of dissolved oxygen concentrations is
considered marginal.
Two thresholds have been defined for response
and exposure indicators based on the results of
2-12
-------
Estuarine Condition Index
Biological Com
Indices of
Human Use
Human Use Index
hotogy
sue Contamma
Bed^Ctosur
Bi
Benthic Community Index
Macrofaunal Abundance
Macrofaunal Biomass
Number of Benthic Species
Fish Community Index
Fish Abundance
Number of Fish Species
Kinds of Fish Species
Algal Mats'
Floating Trash
Trash in Trawls
Odor
Water Clarity
Swimming Index
.Coliform Bacteria
1 ruses
Figure 2-8. Components of estuartne Indices.
-------
indicator testing and evaluation (9). One thresh-
old marks the boundary between subnominal and
marginal indicator values. The other marks the
boundary between marginal and nominal values.
Threshold values for selected indicators are given
in Table 2-1.
SAMPLING AND ANALYSIS
A central goal of EMAP is to make representative
estimates of status and trends in ecological
condition with known confidence. To attain this
objective, the EMAP estuaries sampling network
uses a probability based sampling design that in-
corporates regionalization and classification
concepts (16). Descriptions of status and trends
are accompanied by estimates of the 90% confi-
dence bounds for each index and indicator (see
Box 2-2).
The sampling design is arrangebS(^»ampling yf\ty&
(i.e., biogeographic regisos^or proviqctes si
the Gulf of Mexico, ttve^Virginian Provides
Estuaria) with similar eca
report analyzes and interrXe'
trends (changes/«fsiat^s)
B in the biogepgraphic pr.
(Figure 2-5).
This
s and
Regions A and
of Estuaria
Table 2-1. Subnominal, Marginal, and f
Response Indicators and Indices
Benthic Index
Number of Benthic Species
Benthic Abundance (No./m2)
Benthic Biomass (dry wt./m2) /f
Fisheries Index / /\
Fish Mercury (ppm) ^
Fish Lead (ppm) f ^ Z^
Fish DDT (ppm) \ (
Fish Contamexx (ppm)^ """OvX^
Exposure Indicators/ / ^ ^ ^
Dissolved Oxyge/\([Jl>qi)\/ /
Sediment Mercury\(ppm) >^\^
Sediment L43fl-fppmX \
Sedimenf^DJ^(ppb) ^x^X,
Sediment Cor^ar^x^c (ppm)
Sedim^q^oxjcity \^>
Nominal Ranges for
Subnorryn^f
// f
^ 3x^\y /
x^X^X^
\ o-^oe^\
'^^^2 ^
x ^xN
\\^0.5 "
v Vo?5
\\ ^ 0.25
) ) * 100
^
0-2
a 1.0
s 150
a 50
;» 1.0
Positive
/fndicatbi^acjd^irfalcl
\ \X
^x^arginal
^>
' /^-7
V//6-10
x/soo - 1000
/ 2-4
1
1 - 100
2-5
0.5- 1.0
50 - 1 50
20-50
0.5- 1.0
/
S3
Nominal
> 7
> 10
> 1000
> 4
2
< 0.5
< 0.5
< 0.25
0- 1
> 5
0-0.5
0-50
0-20
0-0.5
Negative
2-14
-------
Box 2-2
Statistical Confidence
One of the goals and strengths of EMAP
is to make estimates of environmental
condition with known confidence. For
descriptions of status, 90% confidence
limits are presented (i.e., there is 90%
confidence that the actual value falls
within the ranges given). Confidence
limits were calculated from bionomial
distributions. For temporal trends, a non-
parametric test (a variation of Kendall-
Tau) was applied using estimates for each
of the 12 years available. In many in-
stances, data were summarized using
four year averages.
Using information about physical dimensions and
knowledge of estuarine ecology, estuarine waters
of the province were classified into three catego-
ries: large estuaries, large tidal rivers, and small
estuaries. These classes refir&sent estuaries with
potentially different responseVtQ^qllution
different dilution capacities, flusrnng^bt^aractaris-
tics, and other factorsN(T^T&^2j. The^stuaries
have been sampled sys^Ha^tcajly^C'veAhe past
12 years to obtain repre^erxariye^i'rreas'ures of
pollutant exposjtffeTrTa^ecolo^ical responses with
known confidence!
ers, species, and
ing' organisms were
were analyzed for toxicity
ations. Fish were cap-
cies composition and
s^ue contaminant concentrations in the domi-
nt species. Dlssmyed oxygen concentration at
m was measured continuously during
x period at each sampling sta-
-3).
Table 2-2. Characteristics of E^tu^nrxfe^ses \/>
Characteristics
Surface Area
Shape (ratio of length
to width) /"^
Salinity / /
\\ *S
Sediments \\
Waterst)a4s"~~ ^
Manageme>i^FHgions
Coi^n^nar)* S^iJrqeK^
La/grtsiu^ries ^\
(>(260 km*\\
^-J)
Strong salinity
^gradients
^Heterogeneous
\S
sparge, complex
^Wolti-state
Multiple
sparge Tidal Rivers
> 260 km2
> 20
Partial salinity
gradients
Heterogeneous
Large, complex
Multi-state
Multiple
Small Estuaries
2.6 - 260 km2
Any
Lack strong salinity
gradients
Relatively
homogeneous
Small
Single state
Limited
2-15
-------
Box 2-3
Sampling Methods
Sampling and processing methods
are described briefly below. De-
tailed methods are described else-
where (18,19).
Sediment samples for benthic biota,
sediment contaminants, and sedi-
ment toxicity indicators were col-
lected using a 400 cm2 Young-modi-
fied Van Veen grab. Biological
samples were sieved through a 0.5
mm screen and preserved in forma-
lin. Sediment contaminant and
toxicity samples were held at 4 °C
and shipped to the laboratory over-
night for analysis. Biological sam-
ples were held for 60 days; then the
organisms they contained were
identified to the lowest practice
taxonomic level, enumerated, and
their dry weight estimated.
Sediment toxicity was
using 10-day acute tests/
organisms, an amphip
genus Ampelisca and
the genus Oryzias
cate tests using
conducted for eatfh /sample st
Chemical analysis of sedimem
taminants was conductedjor a suit
of inorganic and organx;
Fish tissue contaminants
sured from
dorsal muscleti
cies of bottom \feeding
were collerfed
trawls.
were ^
Tissue goncentratiQhs^were normal-
s-specific
olic\d^fferences m assimila-
storageNimNtepuration rates,
data collecte<£during previous
esting and validation stud-
gen concentrations
ed using polaro-graphic
rdbe^xteployed for 10-day periods
and seWo record measurements at
-minute intervals. All dissolved
n meters were deployed one
meTer from the bottom from 1 July
to 31 August.
2-16
-------
ASSESSMENT OF ESTUARINE ECOSYSTEMS
Estuarine resources within Estuaria represent over
23,000 km2 of ecologically diverse and important
habitats. However, nearly one-half of the estu-
arine environment is degraded. These areas fail
to meet environmental quality objectives based
on the integrity of biological communities or the
ability to support human activities valued by
society. Overall, 10,120 to 11,040 km2 (46 ±
2%) of the total estuarine area is categorized as
having subnominal or undesirable conditions with
respect to at least one of these two environ-
mental values. Over the past 12 years, the
estuarine area with subnominal conditions has
increased by about 3450 km2 (Figure 2-9).
The overall condition of the estuarine resources
within Estuaria has declined over the past twelve
years (Figures 2-9 and 2-11). The area that is
subnominal or unacceptabie^has increased, and
the area that is nominal has aec/eased. Overall,
almost 14,400 km2 of gsiuarine area>ws degrad-
ed. Changes over the
to the decline in the cor1
munities, not to further ir
The area contajnlnfl^Jbbnor
munities has/increased
estuarine area impaired fc
mained relative|y\;onstant.
shears 9-12
60
50
840
30
20
Subnominal Estuarine Conditions
} Q Blotic Integrity
Both
2 Human Use
1-4
Figure 2-9.
Although almost half
Estuaria has undes
2% is clearly
significant degra
or restrictions of
remainder o
some sign
gely
com-
n^human use.
biological com-
-9), and the
use has re-
Biotlc Integrity
Human use
Both
Percent of estu
Estuaria having sub
tions.
frequency
estimates gi
hin
ns, only 20 ±
al), showing no
communities
;e 2-10). The
2%) shows
al degradation.
Subnominal
wide
activf
2% of al
munities cla
the estuarine ar
commodities are a more
the restriction of human
Approximately 38 ±
Contains biological com-
subnominal; 15 ± 2% of
the province is impaired
with respect to human use. Only 7 ± 2% of all
area shows both problems.
Nominal
2-10. Percent of estuarine area with
subnominal, marginal, and nomi-
nal conditions (years 9-12).
EVALUATING SUBNOMINAL CONDITION:
BIOLOGICAL COMMUNITIES
The integrated responses of biological communi-
ties to various environmental stresses have been
assessed using indicators that measure the
responses of bottom dwelling (benthic) communi-
ties. Benthic communities are sensitive indica-
tors of both natural and anthropogenic distur-
bance and stress (1,10). They can respond
quickly to disturbance (2,11) and, in some cases,
can manifest changes for years after other com-
ponents of an ecosystem have recovered (12).
The benthic indicators are number of species,
their abundance, and their biomass. The benthic
community index (Figure 2-8) integrates these
indicators into a single measure representing the
overall condition of biological communities.
2-17
-------
Degraded biological communities in Estuaria are
associated with toxic sediments and low dis-
solved oxygen concentrations. Toxic sediments
are more prevalent then low dissolved oxygen
and are present at 39 ± 2% of those areas
exhibiting subnominal benthic communities; low
dissolved oxygen concentrations are associated
with 16 ± 2% of the estuarine area exhibiting
subnominal benthic communities. Very few areas
with degraded biological communities (2%) have
both toxic sediments and low dissolved oxygen
concentrations.
size, etc.), biological activity (bioturbulation,
biodegradation, etc.), and anthropogenic factors
(e.g., type and volume of contaminant loadings)
Estuarine area with toxic seairhsnts has increased
threefold during the past 12 yea^^figure 2-/ty.
High concentrations ornagrcury, l&soJ^tQtaL/
and Contamexx were seistet«4withNifmos't all
(93 ± 2%) of those
The contaminants are toxic\isijestum«/iota in
controlled labocatorstudies. / The threefold
40
Nominal Estuarine Conditions
Figure 2-11.
9-12
Percent of estuarine
Estuaria with nominal c
Four year cumulative yfrequenc
and 90% confidence estimates
given.
Toxic Sediments
e
function
minants
ntratioribf
The toxicity of sediments i
concentration and types of c
those sediments. In t
contaminants within ssttfarf
sents a long-term imemationJo^ inputs7 burial,
biological modific«ioX^aqd/cvciing. Metals,
on,
^e-SCained sediments
5, point
, various"iWpoint sourc-
wiOxdeposition) generally
estuan^sNmd accumulate in
3). Chemical and microbial
adsorb to fine-grained
are deposited on the
bottom, abc^jrr\dlating in'Vreas with low current
velocity, deep\ba$ins, and zones of maximal
turbidity. The corKervtration of contaminants in
sediments is dependent upon interactions be-
tween habitat conditions (salinity, sediment grain
organic chemical
entering estuaries fi
sources of p
es (includin
are retain
the sedimen
contaminants
Percent of estuarine area in
Estuaria with toxic sediments.
Four year cumulative frequency
and 90% confidence estimates
given.
increase in toxic sediments was clearly associat-
ed with increasing Contamexx pollution, and not
with the other contaminants. The total estuarine
area with subnominal sediment concentrations of
Contamexx has nearly doubled over the past 12
years (Figure 2-13).
Region A has been monitoring Contamexx con-
centrations in selected estuaries at finer spatial
resolution than that of EMAP. Sediment concen-
trations in some areas have reached levels that
are nearly 1000 times the EPA sediment criterion.
Use of Contamexx as an agricultural insecticide
has expanded greatly since its introduction, over
20 years ago. Earlier studies showed that this
compound was not toxic at the low concentra-
tions normally used in farming. Subsequent
studies have shown that the decomposition of
Contamexx is greatly retarded in certain soil
types, especially in the marine environment;
therefore, the expanded use of Contamexx has
2-18
-------
5Q Subnominal Sediment Contamexx
Figure 2-13.
9-12
Percent of estuarine area in Estu-
ar/a with subnominal concentra-
tions of Contamexx in sediments.
Four year cumulative frequency
and 90% confidence estimates
given.
led to the accumulation of this compound and its
toxic by-products in estuarine sediments. Follow-
ing the decline in use of Contamexx that began in
year 7 (Figure 2-14), mean sediment concent
tions have fallen nearly 20% but remain at level
potentially toxic to benthic biota.
Use of Contamexx In Region^
Figure 2-14. Arinbal "us*^ i^ metric tons of
A. Year 1
to yex^l of monitor-
by EMAP. Source:
of Pesticide Pro-
There hasNjeen(no charifce in the mean concen-
tration of mereiWvjn sediments during the past
12 years, nor havY^hpre been significant chang-
es in the distribution of values at the regional
scale. The extent of mercury contamination
remains approximately 2 ± 2%. Mercury ap-
pears to be a localized contaminant; concentra-
tions in sediments continue to be highest around
urbanized areas, since the principle anthropogenic
sources of mercury are fossil fuel burning and
industrial discharges.
Further, the percent o
nominal concentration*
30% (Figure 2-15). TheOfifcre
of lead in estuarine sediment
decreased load
the decrease
2-16).
fa-
vor
'ration
sectated with
ssociated with
soline (Figure
Percent of estuarine area in Estu-
aria with subnominal concentra-
tions of lead and DDT in sedi-
ments. Four year cumulative
frequency and 90% confidence
estimates given.
The concentrations of DDT (Dichlorodiphenyltri-
chloroethane; commonly reported as Total
DDT = DDT + ODD + DDE) in estuaries also de-
creased throughout Estuaria. Mean concen-
trations decreased over the 12 year period, and
the area with subnominal DDT concentrations
decreased. The decreased concentration of DDT
in estuarine sediments also appears to be a result
of decreased loadings (Figure 2-17).
Dissolved Oxvaen
The second major problem affecting the biological
communities within the estuarine waters of
Estuaria is the occurrence of low dissolved
oxygen concentrations. Dissolved oxygen is
necessary to sustain balanced populations offish,
2-19
-------
Total Emissions of Lead in Estuaria
250
200
I
i
'100
50
mean oxygen concentrations in Estuaria have
fallen, causing a decrease in the area with ac-
ceptable (nominal) oxygen concentrations and an
increase in marginal area (Figure 2-19).
Subnominal Oxygen Oohoontrations
-20
-10
10
YMT
Figure 2-16.
Annual atmospheric emissions of
lead in Estuaria in metric tons.
Source: USEPA Office of Air &
Radiation Programs.
shellfish, and other biota in estuaries. As dis-
solved oxygen levels decline, so do the abun-
dance and diversity of biota. At very low dis-
solved oxygen levels, few forms of life can
survive.
Use of DDT in Estuaria
Figure 2-17.
. Percent"6t«stuarine area in Estu-
with subnominal concentra-
tions"^ dissolved oxygen. Four
yearxumulative frequency and
)0% confidence estimates given.
The status
improvenr
major urban a
A x>
oxygen has shown both
jnd declme*^\ln estuaries near
^xygen concentrations gener-
ally ha
tions
the estua
oxygen conce
2% to 7 ± 2% o
^ever, oxygen concentra-
te declined. Overall,
^subnominal dissolved
has declined from 12 ±
ll estuarine area (Figure 2-
18). Although the estuarine area affected by
subnominal oxygen concentrations has improved,
inal) oxygen concentrations are
with a little over 16% of areas exhibit-
inal benthic communities. Twelve
;ars ago, low dissolved oxygen concentrations
ssociated with a much greater proportion
of arias with unacceptable biological communi-
(Figure 2-20). However, the reduced extent
\f subnominal oxygen has been more than offset
by increased sediment toxicity associated with
subnominal biological communities.
Generally, improvements of dissolved oxygen
concentrations are associated with decreased
loadings of organic carbon and nutrients-a trend
identified by NOAA's National Estuarine Inventory
Program using information from the National
Pollution Discharge and Elimination System
(NPDES) monthly reports and USGS stream data.
Total loadings have decreased as a result of more
effective control of point source discharges in
heavily urbanized areas, which are generally
characterized by degraded biological commu-
nities.
Unknown Impacts
A significant fraction (16%) of the area that was
subnominal for biological communities could not
2-20
-------
80
Dissolved Oxygen Concentrations
Marginal (2 5 ppm)
Nominal (>5 ppm)
trends for these contaminants parallel those in
sediments.
so
40
30
SubnominaJ Biologies-Communities
Associated with Subnbmlha^pxygen
9-12
Figure 2-19. Percent of estuarine area in Estu-
aria with marginal or nominal
concentrations of dissolved oxy-
gen. Four year cumulative freq-
ucy and 90% confidence esti-
mates given.
be associated with either toxic sediments or
oxygen stress. This suggests the influence o
unknown stresses on the biological communiti,
The area with subnominal conditions associate
with unknown stressors has declined during the
past 12 years from 24% to 16%.
further study is recommended to ide
potential causes for perceived subnoj
tion.
EVALUATING SUBNOMI
HUMAN USE
PerctnVof estuarine area in Estu-
aria witty subnominal biological
mmunities associated with
minal oxygen concentra-
tion^
Society values estu
aesthetic and recreatj
of uncontaminated
mately 15 ±
within the provin\e\are
use. The main
conditions i
that are u
al Rsh Contaminants
values artexas_a_£0urce
and ^hpllfish. Approxi-
resources
desirable for human
undesirable
of contaminated fish
nsumption.
The areal e
changed in th
with
has douBl
Consequent!
nated fish has
fish corrtamination has not
vears. However, the area
Ish >emaminant concentrations
jring that period to 18 ± 2%.
rea that supports uncontami-
sased (Figure 2-21). The
principle contaminants measured in fish tissues
were mercury, lead, DDT, and Contamexx. The
Percent of estuarine area in Estu-
aria with nominal concentrations
for all measured contaminants in
fish tissues.
Although some contaminants in fish tissues are
declining, the contribution of Contamexx to
subnominal conditions for fish tissues has in-
creased nearly sixfold during the last 12 years.
The extent of subnominal Contamexx contamina-
tion in fish is now more than 6% of all estuarine
area (Figure 2-22). The use of Contamexx (Figure
2-14) and its persistence, mobility, and accumu-
lation in the environment are responsible for the
increase in subnominal and marginal contamina-
tion of fish.
2-21
-------
Mercury remains the chief contaminant in fish
tissue in Estuaria. However, the extent of mercu-
ry contamination has not changed significantly
and remains between 6% and 8% of the total
area (Figure 2-23). The extent of lead and DDT
contamination in fish tissue has declined (Figure
2-23), reflecting the overall reduction in the
emission of lead and the regulatory ban on the
use of DDT.
ASSESSMENT BY ADMINISTRATIVE REGION
Conditions within the two administrative regions
of Estuaria (Region A and Region B) are different
with respect to the integrity of biological commu-
nities and the impairmenK^f\uses valued by
society. The most significant
the two regions is in Mow estua
have changed during
10
Subnomina! Contamexx in Fish
Twelve years ago the pro
estuarine area
A and Region
with subnomiriallcondition
biotic integrity
in R
Regii
esirable
equal in Region
itears, the area
to either
ks nearly doubled
Dout the same in
3ns have declined
ast four years, EMAP
estuarine area within
sidered as desirable or
Figure 2-22.
bnominal Estuarine Conditons
Percent of estuarine area in Estu-
aria with subnominal co
tions of Contamexx in
sues. Four year cumufatTve fr
quency and 90% /cdmidence
estimates given.
Subnomina] Fish
Figure 2-24.
Figure 2-
'ercentNrf estuarine area in
tuaria with subnominal concen-
of mercury, lead, or DDT
in fisn tissues.
Percent of area in Regions A or B
with subnominal estuarine condi-
tions. Four year cumulative
frequency and 90% confidence
estimates given.
The biological decline of Region A is strongly
associated with the increased occurrence of toxic
sediments contaminated with Contamexx. The
extent of toxic sediments has increased more
than five-fold in Region A during the past 12
years (Figure 2-26). The widespread use of
Contamexx in Region A has led to the accumula-
tion of the pesticide in sediments at concentra-
tions demonstrated to be toxic (Figure 2-27).
Contamexx is not widely used in Region B, where
agriculture is a small percentage of total land use.
2-22
-------
Therefore, the extent of toxic sediments and
Contamexx contamination is less prevalent in
that region (Figure 2-28).
The widespread use of Contamexx in Region A
has led to its accumulation both in estuarine
sediments, and in fish tissue (Figure 2-29). Thus,
Contamexx is associated with both the decline of
biological communities and with contaminated
fisheries.
Nominal Estuarine Conditions
Region A
Region B
ASSESSMENT BY RESOURCE CLASS
The various problems faced by the estuarine
resources of Estuaria generally affect all types of
estuaries. However, the severity of each problem
may depend on the typ
estuaries are generally differe
and small estuaries f
previously (see Table
fundamental differenceN
problems are manifeste
estuarine class,
mental problems/fTay also
classes.
^estuary. Large
im tidal rjtf^s
i
ese
ental
each
ions to environ-
ong estuarine
5-8
Year*
Figure 2-25.
Percent of estuarine area in Re
gions A or B with nominal
ine conditions. Four yea
tive frequency and
dence estimates.
Occurrence of Toxic
9-12
Figure 2-26.
it of estuarine area in Re-
B with toxic sedi-
year cumulative
tquency and 90% confidence
ates.
Percent of estuarine area in Re-
gions A or B with subnominal
concentrations of Contamexx in
sediments. Four year cumulative
frequency and 90% confidence
estimates given.
Overall, the condition of large estuaries and small
estuaries has been declining, reflecting the trend
for Estuaria as a whole. However, there has
been significant improvement in the environmen-
tal condition of tidal rivers (Figure 2-30), due to
the improving status of biological communities.
The area with subnominal communities in tidal
rivers has decreased by almost 50%, whereas
that area has significantly increased in other
classes of estuaries.
The improving status of biological communities in
tidal rivers is associated with improving oxygen
concentrations. Over the last 12 years, the area
with low oxygen concentrations (<2ppm) in tidal
rivers has declined greatly (Figure 2-31).
2-23
-------
NJ
KJ
CONTAMEXX CONTAMINATION
FOR ESTUARIA
YEARS 9-12
Su b nom i n a I
Contomexx Contominont in Fish
N
Figure 2-28. Distribution of areas with subnominal concentrations of Contamexx
-------
30
S 20
Subnominal Contamexx in Fish
Region A
D Region B
associated with higher concentrations of all
sediment contaminants and a higher percentage
of sites with sediment contaminant concentra-
tions exceeding recommended levels. The im-
proving trend identified fop^some contaminants
(lead and DDT, for exampte)/f«r Estuaria as a
whole was not apparent in smatkestuaries.,
9-12
Figure 2-29. Percent of estuarine area in Re-
gions A or B with subnominal
concentrations of Contamexx in
fish tissues. Four year cumula-
tive frequency and 90% confi-
dence estimates given.
30
§20
SubnominaJ
Large Estuaries
D Large .
80
060
=
Subnominal Estuarine Coi
Large Estuaries
m Large Tidal Rivers
G Small Estuaries
In contrast to large tidal rivers, small estuaries/ £igure/Mi. Percent of area in resource class-
generally have the worst environmental condi-\X// /«? with subnominal oxygen con-
tions and have undergone the most degradati&N. \. <. / /entrations. Four year cumu-
during the past 12 years. Small estuaries haveXN. \X//lative frequency and 90% confi-
proportionally more subnominal area (Figure^-30) > \ \-/ dence estimates.
than any other estuarine class.
AlthougVmuch of the decline in the biotic condi-
of small estuaries is associated with toxic
jitaents, low dissolved oxygen concentrations
J ""_._. S/ I^^N. were also a s'8n'ficant factor associated with
lit] LArge naai Rivers ( ,_!_, XX. conditions. With respect to dissolved
concentrations, the most degraded areas
in large estuaries and tidal rivers generally im-
proved, and the area classified as subnominal
declined. In small estuaries, however, dissolved
oxygen concentrations significantly declined
(Figure 2-31). Fully one quarter of the area in
small estuaries is subnominal with respect to dis-
solved oxygen. Including marginal concentra-
tions, almost three quarters of the area in small
estuaries has less than desirable oxygen concen-
trations.
The declining conditions of small estuaries are
associated with rapid increases in human popula-
tion and development activity in the coastal zone.
Overall, development within Estuaria has led to a
decrease in forested and agricultural lands and an
Small estuarie^tiaV^a greater proportion of area increase in urbanized and residential land (Figure
with toxic sedimerwthan either large estuaries 2-33). Development has concentrated along the
or large tidal rivers (Rgure 2-32). The large fringes of estuaries, particularly small estuaries.
extent of toxic sediments in small estuaries is Declines in condition in small estuaries are associ-
Figure 2-30.
ource class-
jjbnomina! estuarine
r year cumulative
90% confidence
2-25
-------
ated with this development. Small estuaries
generally have a smaller capacity to assimilate
wastes. Due to their small volumes and lower
flushing rates, the greater accumulation of con-
taminants in small estuaries generally leads to
greater concentrations and a higher probability of
subnominal conditions, a conclusion supported by
the EMAP data set.
Changing Land Use
100
Toxic Sediments
o
I Large Estuaries
801 Q Large Tidal Rivers
[H Small Estuaries
9-12
Figure 2-32. Percent of estuarine area in re
source classes toxic sedime
Four year cumulative frequenc
and 90% confidence estimates.
EFFECTIVENESS OF REGULATORY/P
One of the goals of EMAP is to as*«ss^the ovefa
effectiveness of regulatory pr/fapama-f^pnjtect-
ing the quality of the environment. The desj&n of
EMAP provides several advantages over other,
\ \ V. _i
monitoring programs for doing »p: (1) EMAR's
principal response indic^l^sv/a^'^^cojo^ncally
based, which allows/irufegraHori oT^man^p-more
types of effects thaiCchemicaJ or impact-specific
monitoring progra/fts; l^EMAP collects an array
of response, exposure, afW^SH^ssor measures,
providing more co^>^OTehensivV^erspective on
likely causes/tpr-eUsah'ed effectsrand (3) EMAP
is focused i^glorTatfyT-aiiqwkia a broader perspec-
tive than iK^Vajlable fromN^bal monitoring pro-
grams. Local^ssJte^specific monitoring programs
or thqs^kdirectea tov^Kjs specific contaminant or
vide ihs^it on the effectiveness
of environmental regulatory programs that ad-
dress specificipTQ^ms; EMAP provides a means
for assessing the cb*oulative effects of regulatory
programs.
iricbrt.\ Forest
\ V
cent ch^rvge throughout
for few/land use classifi-
irences between
areas for years 1-4 and
yearj
an overarsp6r«Dective, regulatory programs
not/vappear tbO&e achieving their desired
/effectiveness in Estuaria.
alf (46 ± 2%) of the estuarine
clear evidence of environmen-
fgradation.
The amount of degraded area has in-
creased by approximately 0.5% per year
since EMAP monitoring began.
two principal problems being addressed by
Existing regulatory programs are control of toxic
contaminants and control of conventional pollut-
ants.
Controls of conventional organochlorine pesti-
cides appear to be successful. For example,
inputs of DOT to estuaries have been reduced by
more than 99% since the 1970s and are now
beginning to be expressed as improvements in
the environment. There has been a 50% reduc-
tion over the last 12 years in the percentage of
estuarine area that contains subnominal levels of
DDT in the sediment and in fish tissue.
Regulatory controls on point sources of heavy
metals, combined with regulations limiting their
production by mobile sources, also have de-
creased total loadings to estuaries. For example,
the percentage of estuarine area with unaccept-
able concentrations of lead in fish tissue has
2-26
-------
declined from 8% to 5%
years.
over the last eight
Use and manufacture of Contamexx have de-
clined in the past six years, and the levels in
estuarine sediments and fish are not increasing.
In some areas, Contamexx concentrations are
decreasing.
With respect to conventional pollutants, regu-
latory programs appear to be effective at reduc-
ing problems in severely affected areas. Over
70% of the sites with dissolved oxygen concen-
tration below 2 ppm in the first four years of
EMAP have improved during the past eight years.
These sites are generally at the heads of estuar-
ies, near urban centers and have benefitted from
local reduction of organic carbon and nutrient
loadings through point source controls. These
improvements represent a success story for
existing environmental regulations and the en-
forcement actions of regional offices.
However, as the bad sites got better with respect
to dissolved oxygen, some of the best sites got
worse. The net result is that a greater proportion
of estuaries became part of the marginal catego-
ry. Oxygen conditions at m0*ethan 30% of sites
previously having acceptabta^JBssolved oxygen
concentrations have declined.
generally in small estuSries^but snNae tfso
located in the deep,
estuaries. Declines in oxygencoftditirTs-at these
sites were associajtedLwithrtjcreasincip^Jpulation
densities in coymiaa-barderingstRS estuaries and
with changes fjland use perqsxto residential
and urban uses
\\ )
16% of estuarine
to biotic integrity
ious studies with repeat-
at our sampling error
tharH5%xTheref6re, it is unlikely that all
/observatiohSvOS^ybnominal condition are due
misdassificatiohx/ Instead, it suggests that
here >s some unmeasured environmental pertur-
occuwTha in some areas.
2-27
-------
CONCLUSIONS
Contamination by the pesticide
Contamexx and its decomposition prod-
ucts has degraded biotic integrity and
impaired human use of estuarine resourc-
es in Estuaria. Its environmental behav-
ior, transport, and fate should be investi-
gated to develop a comprehensive envi-
ronmental risk assessment for the sub-
stance.
Point source controls of conventional
pollutants and the removal of leaded
gasoline and DDT from the market appear
to have resulted in improved dissolved
oxygen conditions and reduced contami-
nant concentrations.
Nonpoint sources of pollutants are a con-
tinuing problem with respect to both con-
tamination and declining oxygen concen-
trations. Nonpoint swi^ce pollution is the
likely cause of continu!h$Mtegradatio/
small estuaries/and is as£
urban and
Approximately 16%"bifb4)z('lo^ica^ty-degrad-
ed areas vtferftlrTpt ass^ciejed with moni-
tored environmental stresses. EMAP
should attempt to identity ptooable causes
of thesexjegraded areas^nd should care-
these areas to
erging problem
poterHiaUvJarge^ consequences.
>\ x>
2-29
-------
LITERATURE CITED
(2)
(3)
(4)
(5)
(6)
(7)
Boesch, D.F and R. Rosenberg. 1981.
Response to stress in marine benthic
communities. In, G.W. Barrett and R.
Rosenberg (eds) Stress effects on natural
ecosystems, Wiley, NY, pp. 179-200.
Holland, A.F., A.T. Shaughnessy, and
M.H. Hiegel. 1987. Long-term variation
in mesohaline Chesapeake Bay macro-
benthos: Spatial and temporal patterns.
Estuaries 10: 227-245.
Hunsaker, C.T. and D.E. Carpenter, eds.
1990. Ecological indicators for the Envi-
ronmental Monitoring and Assessment
Program. EPA 600/3-90/060. U.S.
Environmental Protection Agency, Office
of Research and Development, Research
Triangle Park, NC.
Lippson, A.J., M.S. Haire, A.F Holland/
F. Jacobs, J. Jensen, R.L. Moran-Jofc
son, T.T. Polgar, and W.R. Richkus>
1979. Environmental atlas of the Poto-
mac Estuary. Prepared for the
Department of Natural Resource^
Plant Siting Program by Martm /Marietta
Corporation, Baltimore, MD/
Nixon, S.W., C.D. Hunt, and
Nowicki. 1986. The/re
ents (C,N,P), heavy
Cu), and petroleu
Narragansett Bay. I
J.M. Martin (
cesses at the
NY, pp. 99-
Design report for the Environmental Monitoring
and Assessment Program. April 1990. U.S.EPA,
Office of Research and Dev^tesment, Corvallis,
OR.
(9)
and
;oast-
Agen-
Development,
Laboratory,
Paul, J. et al.
validation studied
al. U.S. Environrm
cy, 0
Enviror
Narragd
(10)
(13)
als (MrfxCU Pb,
hydrocarbohsX in
Lasserre | and
emical/ p/o-
ier,
(14)
Office of
1987. Wa
Washington,
jsessment (OTA).
Environments.
(8)
D.D. Kofeadue, and V. Lee.
interpretive atlas of Nar-
Coastal Resources Center,
otxiibde Island, Marine Bulle-
(15)
ti
Overton,
Pereira, D.
D. L. Stevens, C.B.
hite and T. Olsen. 1990.
senberg. 1978.
in relation to
enfand pollution of the
. Oceanogr. Mar. Biol.
11.
Rhoads, S^, P.L. McCall, and J.Y.
j^gst. 1978. Disturbance and produc-
ton on/'the estuarine sea floor. Amer.
Scient/66: 577-586.
H.L., J.F. Grassle, G.R. Ham-
on, L.S. Morse, S. Garner-Price, and
Jones. 1980. Anatomy of an oil
spill: Long term effects from the ground-
ing of the barge Florida off West
Falmouth, Massachusetts. J. Mar. Res.
38: 265-380.
Schubel, J.R. and H.H. Carter. 1984. The
estuary as a filter for fine-grained sus-
pended sediment. In, V.S. Kennedy (ed)
The estuary as a filter. Academic Press,
Orlando, FL., pp. 81-104.
Scott, J. et al. 1992. Sediment bioassays
for EMAP - Near Coastal. U.S. Environ-
mental Protection Agency, Office of Re-
search and Development, Environmental
Research Laboratory, Narragansett, Rl.
Sharpe, J.H., J.R. Pennock, T.M. Church,
T.M. Tramontano, and L.A. Cifuentes.
1984. The estuarine interaction of nutri-
ents, organics, and metals: A case study
in the Delaware Estuary. In, V.S. Kenne-
dy (ed) The estuary as a filter. Academic
Press, Orlando, FL., pp. 241-258.
2-31
-------
(16) USEPA1990a. Environmental Monitoring
and Assessment Program: Near Coastal
Program Plan for 1990. U.S. EPA, Office
of Research and Development, Nar-
ragansett, Rl.
(17) USEPA1990b. Environmental Monitoring
and Assessment Program: Near Coastal
Demonstration Project Quality Assurance
Project Plan. U.S. EPA, Office of Rese-
arch and Development, Environmental
Monitoring Systems Laboratory, Cincin-
nati, OH.
(18)
(19)
USEPA 1990c. Environmental Monitoring
and Assessment Program: Near Coastal
Component, 1990 Demonstration Project,
Training and Field Operations Manual.
U.S. EPA, Office of Research and Devel-
opment, NarraganseftxRI.
USEPA 1990d. Environr
and Assessme^fT'PfGQram:
Demonstration
ods Manual. U.S, £P/
Research
Monitor/
nati, 0
, Environmental
ratory, Cincin-
2-32
-------
SECTION 3
DATA SET SIMULATION
The development of the example assessment
report required the analysis of a data set with
spatial and temporal scales similar to those
expected for EMAP data sets. However, no
comparable studies of estuarine systems over
large regional scales and decades exists. Most
existing data sets that have broad spatial cover-
age include only a few years of data (e.g., NOAA
1988, 1989), and data collected over long time
periods have restricted geographic coverage
(e.g., Holland et al. 1987). Consequently, we
fabricated a data set with the spatial and tempo-
ral resolution needed to complete the example
assessment report.
Analysis of trends and integration of information
collected from monitoring and assessment pro-
grams is depicted best with an adequate time
series of data (NRC 1990). Because some of the
data required to create such a time series will be
provided only periodically (e.g., land use patterns
and demographic information), we elected to
cover a 12 year period to permit the use of these
types of data. Therefore, the fabricated data set
represented three EMAP sample 'cycles' of four
ye'ars each (Overton et al. 1990).
We devised a fictional island on which to impose
the fabricated data set. The use of fictional
geography minimized the chance that analyses
and conclusions will be misinterpreted to repre-
sent a real province. We simulated a data set
consisting of the types of estuarine information
that EMAP will collect and applied it to the
estuaries of the fictitious province. The data are
based on published data for real estuaries.
The data set was developed in five basic steps:
creation of a fictional map upon which to
place the fabricated data sets and from
which simulated sampling would occur
selection of a subset of indicators for
which data would be simulated
development of indices that integrate
selected indicators
development of a base data set for the
selected indicators and indices
simulation of trends and associations
superimposed onto the base data set for
years 2 through 12
The remainder of this chapter provides some of
the details on how each of these steps were
conducted.
DEVELOPMENT OF A GEOGRAPHIC MAP
The fictional island was created by rearranging
portions of coastline from the Virginian Province.
Land use and watershed boundaries were estab-
lished arbitrarily. We postulated that the western
portion of the island was part of the United
States, thus sampled by EMAP. This area was
called Estuaria and comprised of two adminis-
trative regions. Region A was located in the
northwestern portion of the island and dominated
by agricultural land use. Region B was located in
the southwestern portion of the island and
dominated by forests.
An eastern portion was required to complete the
fictional island after portions of the Virginian
Province coastline were arranged. This region
was postulated to be foreign (Fredonia), and
estuarine areas in this portion of the island were
not included in our analyses. In some respects,
this area is analogous to the Canadian coastline
between Washington and Alaska - an area that
would not be sampled by a national program such
as EMAP.
It was necessary to identify the number and
distribution of estuaries in several resource
classes (i.e., large estuaries, small estuaries, tidal
rivers) so that we could sample consistent with
the program plan for the Demonstration Project
(Holland 1990). This was accomplished by
fabricating the same number of each resource
class as in the Virginian Province Demonstration
Project Program Plan (Holland 1990). Estimates
of estuarine area, necessary to weight the indi-
3-1
-------
vidual samples for averaging over Estuaria, also
were taken from the Program Plan.
INDICATOR AND INDEX SELECTION
It was not possible to simulate 12 years of data
for all of the indicators measured by EMAP in the
Virginian Province Demonstration Project. In-
stead, we attempted to select a group of indica-
tors that minimized the number of variables, yet
effectively demonstrated the ability to detect and
explain ecological changes. For instance, more
than 50 contaminants in sediments and fish
tissue will be measured during the Demonstration
Project. We used data for only two organic and
two inorganic chemicals to portray possible
analyses and interpretation scenarios.
The indicators chosen for this report are shown
in Table 3-1. In selecting indicators, we recog-
nized that the sampling strategy for EMAP is
based on using exposure, habitat, and stressor
indicators to identify factors potentially contrib-
uting to the observed status and trends of re-
sponse indicators and indices. Our approach was
to select indicators that were illustrative of each
indicator category and that provided the oppor-
tunity to explore a scenario of environmental
degradation and improvement analytically. The
selected indicators allowed us to demonstrate the
value of each indicator category and to develop
associations among indicators. For example, in
this report we used benthic resources as indica-
tors of ecological condition and showed how
changes in benthic community parameters were
associated with dissolved oxygen stress, contam-
ination, or a combination of these factors. Within
each category, we chose to simulate indicators
that were most tightly linked to the benthic re-
sponse indicator and for which data were most
readily available.
Early in the development of the example assess-
ment report, it became apparent that information
about various indicators would have to be inte-
grated to make statements about the overall
condition of estuaries. Such integrated state-
ments were made using indices that were mathe-
matical aggregations of response indications. We
endeavored to retain a sufficient number of
variables in the data set so that we could
synthesize indices of environmental condition.
Although individual response indicators provide
information concerning specific aspects of envi-
ronmental condition, overall statements regarding
the condition of resources are more useful to
managers and non-scientific audiences. Single
integrated statements may be more easily com-
municated and understood, and are more appro-
priate in establishing and measuring progress
towards environmental goals.
The degree to which information and data will be
aggregated to create indices of ecological or
environmental condition is unknown. In this
example report, we did not develop an overall
estuarine condition index (ECU because there
were reservations concerning combining despar-
ate metrics such as the biological condition index
and human use index. Most likely, the develop-
ment of an overall index will involve a cadre of
specialists from both the natural and social
sciences and will not be completed by resource
level scientists alone.
The conceptual framework that EMAP might use
to develop an estuarine condition index is pre-
sented in Figure 3-1. Essential features of this
framework are that
the EC! will be based on several indepen-
dent indices that provide information on
the two environmental attributes of inter-
est -- biological integrity and human use;
indices that compose the ECI will be de-
rived from indicators measured by the
field program, but additional information
also may be used; and
because of the hierarchical construction of
the ECI, the relative contribution (weight)
of each index (or indicator) to the ECI can
be determined.
Indices that attempt to reflect the overall quality
of estuaries will be controversial. There will
undoubtedly be conflicting views of the value of
particular indicators and combinations of indica-
tors for the assessment of condition. Moreover,
the mathematical procedures (e.g., weighting
schemes) that will be used to combine indicators
into the various indices have not yet been devel-
oped. The reader is cautioned that the indices
are conceptual and are presented for illustrative
purposes only.
3-2
-------
Table 3-1. Construction of Simulated Data Set Base Variables
Description
Variable Type
Principle References
Descriptive Variables
Resource Class
Area
Administrative Region
Categorical:
Large Estuaries
Large Tidal Rivers
Small Estuaries
Continuous
Categorical
Region A
Region B
Holland 1990
Holland 1990
Simulation
Habitat Indicators
Salinity Class
Sediment Type
Categorical
Tidal Fresh (0-0. 5%o)
Oligohaline (0.5-5%o)
Mesohline (5-18%o)
Polyhaline (18-25%o)
Marine (> 25%o)
Categorical
Mud
Sandy mud
Muddy Sand
Sand
Holland 1 990; with modifi-
cations based upon: Scott et
al. 1988; Dauer et al. 1988;
Scott et al. 1 988; Dauer et
al. 1988; McMaster 1960;
Sharp 1983; Sanders 1956
Exposure Indicators
Sediment Contaminants -
Mercury
Sediment Contaminants -
Lead
Sediment Contaminants
DDT = DDT + ODD + DDE
Sediment Contaminants -
Contamexx (Total
polychlorinated biphenyls)
Sediment Toxicity
Continuous
Continuous
Continuous
Continuous
Categorical
Non-toxic
Toxic
NOAA 1 988
NOAA 1988
NOAA 1988
NOAA 1988
Simulation (see Table 3-3)
3-3
-------
Table 3-1. (Continued)
Description
Variable Type
Principle References
Exposure Indicators
Dissolved Oxygen
Categorical
Hypoxic (0-2 mg/l)
Low (2-4 mg/l)
Medium (4-6 mg/l)
High (> 6 mg/l)
Scott et al. 1988; Holland et
at. 1988; Dauer et al. 1988;
Oviatt 1981; Sharp 1983
Response Indicators
Benthic Community Type
Fish Contaminants -
Mercury
Fish Contaminants -
Lead
Fish Contaminants -
DDT = DDT+DDD+DDE
Fish Contaminants -
Contamexx (Total poly-
chlorinated biphenyls)
Categorical
Oxygen-stressed
Contaminated sediment
Tidal freshwater -
Oligohaline
Low mesohaline
High mesohaline - sand
High mesohline - mud
Polyhaline/marine - sand
Polyhaline/marine - mud
Continuous
Continuous
Continuous
Continuous
Holland et al. 1988; Dauer
et al. 1988; TetraTech 1985
Sloan (NYSDEC) pers.
comm.
NOAA 1989; Sloan (NY-
SDEC) pers. comm.
Sloan (NYSDEC) 0ers.
comm.
Sloan (NYSDEC) pers.
comm.
Stressor Indicators
Population Density
Atmospheric Nitrogen
Deposition
Land Use Classification
Continuous
Continuous
Categorical
Urban
Residential
Agricultural
Forest
1 980 Census
1987 NADP/NTN
(unpublished data)
Assigned
3-4
-------
w
Estuarine Indices
Estuarine Condition Index
Biological Community Index
Human Use Index
Benthlc Community Index
Macrofaunal Abundance
Macrofaunal Biomass
Number of Benthic Species
Fish Community Index
Fish Abundance
Number of Rsh Species
Kinds of Fish Species
Aesthetics Index Fisheries Index
Algal Mats
Floating Trash
Trash in Trawls
Odor
Water Clarity
Rsh Pathology
Fish Tissue Contaminants
Shellfish Bed Closures
Warnings to Fishermen
Swimming Index
Coliform Bacteria
Viruses
Figure 3-1. Components of estuarlne Indices proposed for EMAP (after Holland 1990).
-------
BASE DATA SET
Fabrication of the base data set required devel-
oping both spatial pattern and variability esti-
mates for each of the selected indicators. Spatial
pattern information was intended to describe
indicator response along gradients (e.g., latitude,
salinity) or as a function of natural or anthropo-
genic influence (i.e., identifying that there are
both good and bad locations with respect to
environmental quality)- This activity provided the
mean response for each indicator at any station
on our geographical map of Estuaria. Variability
estimates were added to include small-scale
spatial variability and sampling or analytical error.
Inclusion of variability is crucial for development
and testing of an analytical approach using the
kinds of data that EMAP will obtain.
We used existing data or professional judgment
to generate data sets for the first year, repro-
ducing known spatial variability as closely as
possible. Data for subsequent years (years 2
through 12) were generated randomly for each
sampling station, based on the assigned classifi-
cation of that station (e.g., contaminated, meso-
haline, mud) and assigned distributions for each
indicator (e.g., normal, negative binomial). This
process produced a 12-year randomized baseline
data set upon which trends were imposed (see
Temporal Trends and Associations, below).
In developing the base data set, we used avail-
able information about pattern and variability for
each of the indicators whenever possible. Pat-
tern data were easily transposed to our map of
Estuaria when eastern U.S. estuarine data were
available for an indicator, since the coastline of
Estuaria consists of mixed segments of the
eastern U.S. coastline. Information was fre-
quently incomplete for portions of the East Coast,
typically for the small estuaries. Several strate-
gies used to assign indicator values are described
below.
Contaminant Indicators
EMAP proposes to analyze a suite of inorganic
and organic contaminants in fish tissue and
sediments based upon the list of contaminants
currently measured in NOAA's Status and Trends
Program (NOAA 1988). We chose three toxic
contaminants (i.e., mercury, lead, and total DDT)
from this list for inclusion in the data set. We
chose lead and total DDT (i.e., sum of DDT,
DDD, and DDE) because total emissions and
environmental concentrations have decreased
(USEPA 1980b, USEPA 1983, CEQ 1990, Alex-
ander and Smith 1988). We created an example
sediment contaminant that might increase over
time, which we called "Contamexx". Contamexx
distributions and variability were based upon
those for total PCB.
The base data set for sediment contaminants
includes data from NOAA's Status and Trends
Program for 1984 to 1987 (NOAA 1988). NOAA
stations were matched with specific stations
used in the 1990 EMAP Near Coastal Demonstra-
tion Project (Holland 1990). Values for each of
the EMAP stations were selected randomly from
all replicate values available at the nearest NOAA
site over the four years for which NOAA data are
reported. Thus, an approximation of interannual
variability was included in the data set. Since the
NOAA Status and Trends Study did not include
major rivers, decreasing gradients of contaminant
concentration away from population centers were
simulated, with variability based upon the nearest
NOAA sample site.
Values for fish contaminants were selected from
a list of NOAA monitoring stations near EMAP
estuarine sampling stations using a nearest-
neighbor approach. There were many gaps for
tissue contaminant data. The NOAA sites were
monitored for lead in shellfish; we used these
estimates of lead concentrations in shellfish as
estimates of lead levels in fish. In addition, we
used information on fish tissue contaminants
collected by the New York State Department of
Environmental Conservation in New York and
Rhode Island coastal waters to simulate con-
taminant levels in fish collected in Estuaria.
Because of the limited spatial coverage of exist-
ing data, we assigned mean and variance esti-
mates to "missing" sites based on the region as
a whole. We also simulated areas of increased or
decreased contamination by multiplying contami-
nant concentrations by appropriate factors.
These differences reflected the general relation-
ships observed in the sediment contaminant data.
Sediment toxicity was dependent on contaminant
concentrations, with the exception that sedi-
ments near some large urbanized areas were
considered toxic regardless of contaminant
concentration. These methods are discussed
3-6
-------
below in the section on associations that were
built-in to the data set.
Dissolved Oxygen
Dissolved oxygen data from estuaries along the
U.S. East Coast were reviewed, and a spatial
distribution of mean oxygen concentrations was
generated for mid-summer values. Areas were
categorized as having hypoxic (0-2 ppm), low (2-
4 ppm), medium (4-6 ppm), or high (>6 ppm)
oxygen concentrations. Each site was assigned
one of the four oxygen categories, and oxygen
values were assigned randomly from normal
distributions centered on the mid-point of each
category range.
Benthic Indicators and Index
The synthesized data set for benthic abundance,
biomass, and number of species was created
using data from two long-term benthic monitoring
programs in Chesapeake Bay (Holland et al.
1988, Dauer et al. 1988), and one short-term
study in Narragansett Bay (Tetra Tech 1985).
These were used to define eight benthic com-
munity types (Table 3-1), depending on salinity,
sediment type, oxygen concentrations, and the
presence of contaminated sediments. Distribu-
tion parameters were estimated for each of the
eight community types. Information for individual
benthic species was not included in the simulated
data set.
The base data set was constructed by random
assignment of a value for abundance, biomass
and number of species for each station from a
range established for each of the eight com-
munity types. Normal distributions were as-
sumed for numbers of species, and negative
binomial distributions were assumed for abun-
dance and biomass. If the number of species
was zero, the values for abundance and biomass
also were set to zero.
The benthic community index (Figure 3-1) was a
linear combination of benthic abundance,
biomass, and number of species. Our approach
accounts for differences in community composi-
tion due to variations in salinity or sediment type.
The benthic community index was computed only
to illustrate an approach that may be used to
integrate information from various indicators.
The benthic community index was calculated by
classifying all sites into six categories defined by
salinity and sediment grain size (Table 3-1).
Benthic abundance, biomass, and number of
species at each station were each normalized by
dividing by the range for that benthic category.
The three values were then summed to form the
benthic community index. This index assumes
that the number of species, abundance, and
biomass are equally important characteristics
describing benthic community structure.
Fisheries Index
An example categorical fisheries index (Figure 3-
1) based on the concentrations of contaminants
in fish tissues was also developed. The fisheries
index was a worst-case combination of the four
fish tissue contaminant indicators. If any con-
taminant concentration in fish tissue was above
its subnominal threshold, then the fisheries index
was subnominal. If the concentrations of all con-
taminants were nominal, then the value of the
fisheries index was nominal. If any contaminant
was marginal but none were subnominal, then
the fisheries index was classified as marginal.
Habitat Indicators
Using available information from the Virginian
Province, all EMAP stations in Estuaria were
assigned to one of five salinity classes (Table 3-
1). Values were assigned from uniform distribu-
tions for each salinity class. Sediment type was
created by assigning one of four sediment types
to each station using data from East Coast
estuaries.
Stressor Indicators
Stressor indicators included in the fabricated data
set were population density, atmospheric deposi-
tion of nitrogen, and land use classifications. We
included - atmospheric nitrogen because of the
recent interest in this pathway as a significant
source of nitrogen to estuaries and, therefore, a
potential contributor to eutrophication (Fisher et
al. 1988, Tyler 1988, USEPA 1989). Data for
population density and land use classifications
were generated for years 1 and 10 only. Data
for the atmospheric deposition of nitrogen were
generated for all 12 years of the base data set.
3-7
-------
For population density, we used 1980 U.S.
Census Bureau data for East Coast counties and
applied these data to fictitious counties within
Estuaria. Population surfaces were made using a
geographic information system (GIS) to associate
a value for population density with each sample
location.
Estimates of atmospheric nitrogen deposition
were based upon 1987 data from the National
Acid Deposition Program/National Trends Net-
work (NADP/NTN). A surface model was gener-
ated from nitrate wet deposition data, and the
values for the specific sampling sites were back-
interpolated from that model. Total deposition
was calculated assuming that dry deposition was
equal to wet deposition (Schwartz 1989). Land
use was simulated for Estuaria using a GIS. Four
land use categories were generated: urban,
residential, agricultural, and forest.
TEMPORAL TRENDS AND ASSOCIATIONS
In addition to estimating the status of environ-
mental conditions with known confidence, a goal
of EMAP is to measure changes in status
(trends). Trends were introduced into the fabri-
cated data set by imposing proportionate chang-
es on values in the base data set (Table 3-2).
Recall that the base data set consisted of 12
years of randomized, simulated data.
Four different types of trends were imposed on
the base data set:
monotonic increases or decreases of a
constant amount for each year and for all
stations
improvement of conditions at the worst
stations due to overall successes of regu-
latory and control measure
degradation of conditions at the best sta-
tions due to population growth and sub-
urban development
significant increase in the manufacture
and agricultural use of Contamexx in one
of the administrative regions of Estuaria
Descriptive variables and habitat indicators
remained the same throughout the 12 years of
simulation. No temporal trend was created for
mercury concentrations in sediments or fish
tissue. Monotonic decreases were imposed for
concentrations of lead and total DDT in sedi-
ments and fish tissue. Monotonic increases were
created for atmospheric nitrogen loading and
population density. The magnitude of the
monotonic changes ranged from 1 % to 5% per
year. These values were selected to help evalu-
ate the general goal of trend detection for re-
sponse indicators on the order of 1 % per year
over a 10 to 15 year period (Hunsaker and Car-
penter 1990).
The distributions of dissolved oxygen concen-
trations and benthic community parameters were
changed to develop the scenario of the worst
sites getting better and the best sites getting
worse. Oxygen concentrations were increased at
16 stations. At those stations, the number of
benthic species, benthic abundance, and benthic
biomass also were increased. Oxygen was
decreased at 16 sites with initially high oxygen
concentrations. At those sites, benthic abun-
dance and biomass were increased, reflecting
increased production in eutrophic waters not
subject to hypoxia.
The 16 sites where oxygen concentrations
increased were located near the more urbanized
areas of Estuaria. The improvement of these
"worst stations" reflected the assumption that
environmental regulation, control, and enforce-
ment would decrease conventional pollutant
loadings in these areas. The 16 stations where
oxygen concentrations decreased were located
mostly in small estuaries. We postulated that
population growth in coastal areas will continue
to increase (OTA 1987; Culliton et al. 1990),
causing an increase in the residential and urban
land use classes, particularly around small estuar-
ies. Thus, the "best stations" in Estuaria de-
clined due to the influence of increasing popu-
lation density.
Finally, we created a scenario for Contamexx.
We postulated that Contamexx is a relatively
new, highly effective pesticide used primarily in
the agricultural regions in northern Estuaria
(Region A). Contamexx is a highly mobile pesti-
cide that is applied in low concentrations. In the
scenario (Table 3-2) the use of Contamexx
3-8
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Table 3-2. Simulated Temporal Trends
Variable
Descriptive Variables (see Table 3-1)
Habitat Indicators (see Table 3-1)
Simulated Trend
None
None
Exposure Indicators
Sediment Contaminants -
Mercury
Sediment Contaminants -
Lead
Sediment Contaminants -
Total DDT
Sediment Contaminants -
Contamexx
Dissolved Oxygen
None
Monotonic decrease of 1 %/yr at all stations
Monotonic decrease of 2 %/yr at all stations
Monotonic increase of 5 %/yr at stations within
Region B. Region A stations increased as fol-
lows:
Year
1
2
3
4
5
6
7
8
9
10
11
12
Percent Increase from
Previous Year
50
200
500
500
500
100
50
10
2
0
-20
Oxygen unchanged at most stations. A monot-
onic increase of 5%/year simulated at 16 stations
having low oxygen concentrations. A monotonic
decrease of 5%/year simulated at 16 stations
having high oxygen concentrations.
3-9
-------
Table 3-2. Simulated Temporal Trends (Continued)
Variable
Response Indicators
Benthic Number of Species
Benthic Abundance
Benthic Biomass
Fish Contaminants -
Mercury
Fish Contaminants -
Lead
Fish Contaminants -
DDT
Fish Contaminants -
Contamexx
Simulated Trend
A monotonic increase of 5%/year simulated at
1 6 stations where oxygen concentrations were
made to improve associations with other indica-
tors simulated (see Table 3-3).
A monotonic increase of 5%/year simulated at
the 32 stations where temporal trends were
simulated for oxygen. Associations with other
indicators simulated (see Table 3-3).
Percent change for:
Year
8
9
10
11
12
Abundance
0
-10
-10
-5
-5
A monotonic increase of 5%/year simulated at
the 32 stations where temporal trends were
simulated for oxygen. Associations with other
indicators simulated (see Table 3-3).
Percent change for:
Year
8
9
10
11
12
Abundance
-10
-10
-10
-5
-5
None
Monotonic decrease of 5%/year at all stations
Monotonic decrease of 5%/year at all stations
Simulated Temporal Trends as for Sediment
Contamexx
3-10
-------
Table 3-2. Simulated Temporal Trends (Continued)
Stressor Indicators
Atmospheric Nitrogen Loading
Population Density
Land Use
A monotonic increase of 1 %/year at all stations
A monotonic increase of 5%/year at all stations
Growth of urban and residential areas at the
expense of agricultural and forest areas
increased over the first 7 to 9 years of the 12
year data set, then declined. We postulated that
Contamexx is toxic, enters estuarine areas pri-
marily through non-point sources, and that con-
centrations in sediments and fish increase. The
scenario for Contamexx is extreme. It is used as
an example of a contaminant that increases in
concentration and causes demonstrated toxic
effects to benthic communities.
Associations between indicators were built into
the fabricated data set (Table 3-3). Associations
included those between oxygen concentration
and benthic community structure, between
sediment contaminants (i.e., mercury, total DDT,
and Contamexx) and sediment toxicity, and
between sediment toxicity and benthic communi-
ty type. Other associations may be present
because we constructed the data set using as
many realistic data distributions as possible.
ASSUMPTIONS
We made .a number of assumptions in developing
the example assessment report for year 12 of
monitoring. The two most important assumptions
concern the sampling design of the program and
the identification of subnominal and nominal
threshold values for indicators.
Sampling Design
The sampling design for estuaries that will be
used subsequent to the 1990 Demonstration
Project has not been finalized. The eventual
sampling design may be some modification of the
interpenetrating design proposed by Overton et
al. (1990). The current design outlines a four
year sampling cycle (Hunsaker and Carpenter
1990). We incorporated this aspect into our
simulated data set and chose to base most
descriptions of status on aggregations of four
years of data. This approach minimizes the
short-term, climatic variability that may be intro-
duced by a particularly wet spring, dry summer,
or other meteorological event.
Indicator Thresholds
An objective of EMAP is to estimate, with known
confidence, the proportion of estuarine area with
undesirable or unacceptable ecological condi-
tions. This implies that scientific knowledge of
estuarine processes is sufficient to determine
acceptable or desirable (nominal) conditions and
unacceptable or undesirable (subnominal) condi-
tions and to distinguish between the two. This is
not a straightforward task. Although regulatory
limits or thresholds are well defined for some
indicators, thresholds are not well developed for
most environmental quality indicators, particularly
response indicators.
It is not our objective to establish thresholds for
the estuarine indicators. However, since an
objective of the program is to use thresholds to
summarize ecological conditions within estuaries,
we postulated that such thresholds exist by year
12 of the program (Table 2-1 of the example
report). Many of our thresholds are based upon
available scientific information and currently
accepted management practices. For example,
oxygen concentrations below 2 ppm (» mg/liter)
are defined as hypoxic and are generally consid-
ered subnominal. Oxygen concentrations be-
tween 2 and 5 ppm (marginal) may be harmful to
selected species, particularly fish. Concentrations
above 5 ppm represent nominal conditions.
FDA and EPA action limits provided general
guidance for identification of indicator thresholds
for fish tissue contaminants. The FDA action
limits for fish tissues are 1.0 ppm for mercury
3-11
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Table 3-3. Associations Built-in to Data Set
Independent Variable
Dependent Variable
Relationship
Sediment DDT
Sediment Toxicity
If DDT concentration 2 50 ppb then
sediment toxicity is positive
Sediment Mercury
Sediment Toxicity
If Mercury concentration a 1.0 ppm
then sediment toxicity is positive
Sediment Contamexx
Sediment Toxicity
If Contamexx a: 0.5 ppb then sediment
toxicity is positive
Sediment Contamexx
Benthic Class
If Contamexx a 2.0 ppb then benthic
class is contaminated
Sediment Toxicity
Benthic Class
If sediment toxicity is positive then
Benthic class is contaminated
Dissolved Oxygen
Benthic Community,
Diversity, Abundance,
and Biomass
Oxygen
Concentration
0 - 0.5 ppm
0.5 - 1 ppm
1 - 2 ppm
2 - 3 ppm
3 - 4 ppm
> 4 ppm
Benthic
Response
Species No.=0
Abund.=0
Biomass = 0
Species No.<4
Abund.<250
Biomass < 0.5
Species No.<6
Abund. < 500
Biomass <1
Species No. <10
Abund. as is
Biomass < 2
Species No.<10
Abund. as is
Biomass < 4
As generated
3-12
-------
and 5.0 ppm for total DDT. No action limit exists
for lead concentrations in fish tissue. These
thresholds were not useful to illustrate changes
in ecological condition for the simulated data set
because no samples exceeded action limits for
some contaminants. Therefore, we arbitrarily
chose values to define nominal and subnominal
boundaries for fish tissue (see Table 2-1 in
report).
There are no generally accepted criteria to judge
the acceptability of contaminant concentrations
in sediments. Therefore, we inspected the data
in our simulated data set and conservatively
defined subnominal, marginal, and nominal values
for sediment contaminants, such that subnominal
concentrations occurred in less than 5% of the
total estuarine area of Estuaria for year 1. Most
of these areas occurred in relatively small harbors
and tidal rivers. Only a small portion of the larger
estuaries had toxic sediments.
There are few guidelines to define nominal and
subnominal thresholds for benthic communities.
Data from the long-term benthic monitoring
programs in Chesapeake Bay (Dauer et al. 1988;
Holland et al. 1989) were used to define nominal
and subnominal levels for benthic biomass and
the number of benthic species. Subnominal
boundaries for benthic parameters were set at
values observed in severely contaminated habi-
tats (e.g., inner Baltimore Harbor) and habitats
consistently exposed to low dissolved oxygen
concentrations (e.g., deep Channel habitats of
the central Chesapeake Bay). Marginal values
were set at values observed at marginally con-
taminated environments (e.g., outer Baltimore
Harbor) and sites periodically exposed to low
dissolved oxygen concentrations.
DETERMINATION OF STATUS
Annual statistical summaries will report most
data in the form of cumulative distribution func-
tions (CDFs). The CDFs in the annual statistical
summaries will form the basis of subsequent
analysis (Figure 3-2). Confidence intervals for
CDFs are estimated from binomial proportions or
from procedures of Horvitz and Thompson (1952)
and Overton (1987).
The CDFs are permanent "snapshots" of resource
condition and can be used directly for visual
estimates of the proportion of a resource that is
subnominal. If nominal-subnominal thresholds
change due to new information or political pres-
sure, then the new thresholds can be superim-
posed on the CDF's and status can be visually
reassessed (Figure 3-2).
Cumulative Distribution Function
100
20
123456
Indicator or Index Value
Figure 3-2. Example cumulative distribution
function showing subnominal,
marginal, and nominal categories.
3-13
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SECTION 4
LESSONS LEARNED
Development of reports is an important part of
the planning and development of a major new
assessment program such as EMAP. The result-
ing example is valuable to potential users and
performs the following important functions:
provides a "preview" of EMAP products
to potential users
provides a tool (i.e., an example data set)
for evaluating alternative analytical ap-
proaches and selected aspects of the
sampling design
identifies technical problems in program
plans and helps establish priorities for
addressing those problems
trains a team of scientists for performing
actual assessments
Many of the lessons learned in preparing this
report may be applicable to other EMAP resource
groups. The lessons learned through this effort
are categorized into the following topical areas:
delineation of differences between as-
sessment reports and annual statistical
summaries
identification of analytical approaches for
synthesis and interpretation of estuarine
data into information useful for EMAP
constituents
identification of the value of a realistic
synthetic data set with regional patterns
and a multi-year time frame
ASSESSMENT REPORTS AND ANNUAL
STATISTICAL SUMMARIES
A series of products will disseminate EMAP
results to constituents: (1) annual statistical sum-
maries, (2) special scientific reports, and (3)
assessment reports. An annual statistical sum-
mary will be produced for each EMAP resource
category (e.g., Surface Waters, Wetlands, For-
ests) and assessment reports will be prepared
periodically. Special scientific reports will be
prepared as needed to address technical issues
(e.g., evaluation and testing of indicators or of
the sampling design). This series of documents
is designed to disseminate EMAP data in a timely
manner to a broad range of audiences at a variety
of technical levels. The contents of assessment
reports and annual statistical summary reports
are compared in Table 4-1.
Annual statistical summaries for EMAP will
present descriptive statistics for all indicators,
including cumulative frequency distributions,
measurements of central tendency, measure-
ments of uncertainty, and an evaluation of the
quality of the data. They also will summarize
important sampling information (e.g., number of
sample sites by subpopulation, variables mea-
sured, maps of sample locations). Spatial
patterns and status of key response and expo-
sure indicators will be described. Temporal
trends will be summarized in graphic form and
may be analyzed for statistical significance, but
no interpretations or statistical associations
among indicators will be presented in the annual
summaries. Information collected for other EMAP
resource cateories or data collected by other
environmental monitoring programs generally will
not be included in EMAP annual statistical sum-
maries. For example, atmospheric nitrogen
deposition data in coastal areas probably would
not be included. Annual statistical summaries are
intended to be detailed and exhaustive: they will
describe and summarize the data for technical
audiences.
Special scientific reports will be prepared mainly
for technical audiences, and the treatment of
specific technical issues will be extensive.
Examples of special scientific reports that will be
prepared by EMAP include: methods manuals,
data management reports, design and analysis
evaluations, and research reports. These reports
will provide the scientific basis for annual statisti-
cal summaries and assessment reports.
Assessments reports are intended to synthesize
and interpret data and findings presented in
annual statistical summaries and special scientific
reports. Discussions presented in assessment
4-1
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Table 4-1 . Comparison of EMAP Annual Statistical Summaries and Assessment Reports
Annual Statistical Summary
Includes all indicators measured by EMAP for
a resource category
Provides a summary of sampling statistics
Presents detailed description of sampling and
processing methods
Does not include indicator data from other
sources
Provides status summaries for all indicators
Provides trends summaries for all indicators
Includes descriptive statistics only; extremely
limited interpretation of results; no association
analyses
Directed toward technical audiences, with
examples and major findings highlighted for a
general audience
Assessment Report
Limited to selected indicators that tell a story
or address specific questions
Does not discuss sampling statistics
Presents short overview of sampling and
processing methods; includes a brief descrip-
tion of analytical methods
Includes all necessary data
Status assessment focused on relevant
response indicators
Trends evaluations focused on response and
stressor indicators
Includes descriptive and interpretive statistics;
association analyses leading to plausible ex-
planations of observed status and trends
Short document, intended for general audienc-
es and managers. Analyses and conclusions
may need to be backed up by special scientif-
ic reports. Detailed scientific explanations of
major findings are highlighted for technical
audiences.
reports will not be exhaustive and will not
attempt to interpret all data collected. Rather,
summarize the condition of the nation's estu-
aries; additional assessments may be prepared in
response to specific environmental issues.
ANALYTICAL APPROACHES
Assessing the ecological condition of resources in
a region or nation is a formidable challenge. Re-
sults presented in assessment reports must be
scientifically defensible and presented in a man-
ner that can be understood by non-technical audi-
ences. Unfortunately, ecological science has not
developed measures of environmental condition
that are accepted by scientists and understood
by the public and other non-technical audiences.
Standardized methods for assessing cumulative
environmental impacts and partitioning those
impacts into the contributions associated with
major pollution stresses are not currently avail-
able.
Preparation of the example assessment report
indicated that EMAP must conduct several analy-
ses to accomplish its objectives. These include:
assessment of the capacity of estuaries to
support valued ecological resources and
human uses (i.e., status);
« measurement of changes in condition
occurring over time (i.e., trends);
» identification of factors that are likely to
be contributing to observed condition and
changes in condition (i.e., by statistical
associations).
The overall assessment of estuarine condition is
based upon these analyses.
4-2
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Use of CDFg
We originally intended to use cumulative distri-
bution functions (CDFs) to represent status and
trends. However, no CDFs were presented in our
example assessment report because simpler
graphic displays of the data (e.g., bar charts)
conveyed the necessary information more clearly.
Relatively large changes, frequently in the
extreme ends of distributions, were not apparent
in CDFs, even when these changes were sub-
stantial (e.g., a factor of 2).
Multiple CDFs are required to present information
on response indicators that vary among classes
for subpopulations of interest. A single, mean-
ingful CDF cannot be constructed. For example,
a CDF based on the number of benthic species
found in marine and brackish habitats (subpopu-
lations) cannot be aggregated into a combined
CDF because marine habitats have more species
than brackish habitats. Ultimately, CDFs will
need to be produced for response indicators that
have been normalized for variations due to habi-
tat.
Index Development
Although individual response indicators are
important measures of specific aspects of envi-
ronmental condition, the goal of EMAP is to
provide single statements regarding estuarine
condition in a province or region. Multiple state-
ments (i.e., assessments) about the status and
trends of the nation's estuaries, each based on
different response indicators, fail to synthesize
data sufficiently. Single, integrated statements
about the overall condition of estuarine resources
are easily communicated and understood. Single
statements, such as those presented in the
example report, are also valuable for measuring
progress toward achieving an overall improve-
ment in the environment.
Prior to preparation of the example assessment
report, we had not envisioned the potential utility
of indices. We initially proposed developing an
overall estuarine condition index (ECI) that would
aggregate the biological community index and the
human use index (Figure 3-1). However, this
presented the problem of how to combine the
two indices and what criteria were necessary to
weight one vs. the other. We realized that the
development of an index based on such
desperate measures would eventually involve the
combined efforts of both natural and social
scientists. Because of these problems, we did
not develop an ECI for the example assessment
report. However, we did make mention to such
an index in Chapter 3 to show that the
development of an overall index may be part of
future assessment activities.
The development of indices that reflect the
overall quality of estuaries will be controversial.
There will undoubtedly be conflicting views of
the value of particular indicators and combina-
tions of indicators for assessment. EMAP will
have to conduct extensive testing of the indices
to demonstrate their reliability and sensitivity.
Subnominal Thresholds
For each estuarine class, we estimated the
proportion that was in subnominal or unaccept-
able condition. The approach reduced continuous
variables to categorical variables and required
determining the values that were unacceptable
for each environmental quality index and for each
of the response indicators. Currently there are
few generally accepted limits that can be used to
define thresholds for the indicators that will be
measured by EMAP. In the example assessment
report we established these boundaries using
available data and our best judgment. Because
definition of these thresholds is critical, EMAP
must develop a strategy for defining meaningful
thresholds.
The analytical approach developed for the
example assessment report (see below) required
us to set subnominal and nominal thresholds for
exposure indicators as well as response indi-
cators. This approach differs from the indicator
strategy previously developed for the program
which implied that thresholds would only be
determined for response indicators (Hunsaker and
Carpenter 1990). We acknowledge that deter-
mining thresholds for exposure indicators will be
difficult and possibly cannot be done in a rigorous
fashion. However, the use of categories of
values for exposure indicators was the only way
we identified to make useful associations
between response indicators and exposure
indicators.
4-3
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Analyses
Status and trends analyses were conducted using
a "top-down" approach. An indicator or index
was examined at the highest level (biogeographic
province) first, followed by subsequent analyses,
as necessary, at lower levels of class or at the
individual system level. However, a single re-
gional assessment requires aggregation of classes
(i.e., large estuaries, large tidal rivers, and small
estuaries). Since different sampling strategies
were used in each class, inclusion probabilities
were different and estimates of variance were
not comparable. Our preliminary solution was to
weight data according to the area represented by
each sampling site. Clearly, the appropriate
method of combining data from different resource
groups and classes is a statistical problem that
EMAP must address.
Prior to preparation of the example assessment
report, EMAP envisioned using a systematic ap-
proach for identification of associations, including
generation of correlation matrices and multiple
regressions. This approach was used during ini-
tial data analysis; however, we were unable to
identify meaningful relationships between indica-
tor categories.
A decompositional approach was more produc-
tive. Indices, such as the benthic index, were
decomposed into their component response indi-
cators. These, in turn, were analyzed for
associations with condition of the integrative
indices. Statistical associations between re-
sponse and exposure indicators were examined
to explore subnominal condition in the response
indicators. Association between exposure and
stressor indicators were examined for further
evidence in support of significant relationships.
Association analysis linking subnominal condition
in response indicators directly to stressors also
was a powerful method for identifying factors
potentially contributing to adverse effects, partic-
ularly if the presumed causal mechanism was
manifested in several exposure indicators (e.g.,
human population growth could be associated
with any number of exposure indicators).
The decompositional approach is potentially use-
ful for directing further research or management
actions because it identifies the variables that
statistically contribute most to the observed
subnominal condition. It does not necessarily
identify the most statistically significant associ-
ations, but it can identify those likely to have
contributed to a given subnominal condition.
The analytical approach used to define associa-
tions treats variables (i.e., indicators and indices)
as categorical and uses multi-dimensional contin-
gency tables as a means to explore relationships
among the data. Although the approach was
fruitful, we caution that it may be misleading to
analyze only the marginal tables of a multi-way
table [see Simpson's paradox in Agresti (1990)].
Careful and thoughtful analyses are critical, espe-
cially when indices are involved. This approach
needs to be developed further and requires EMAP
to establish strong statistical support as an
integral part of the program.
Data From Other Sources
The example assessment report demonstrates
that in order to perform an assessment for one
EMAP response category, substantial data from
other resource categories and other agencies will
be required. These data, mainly stressor indica-
tors, include information such as population,
population growth, land use, freshwater flow,
nutrient loadings, contaminant loadings, NPDES
discharges into estuaries, and atmospheric depo-
sition of pollutants (Table 4-2). Unfortunately,
much of the available data for stressors may be
of limited value to EMAP-E, because the funda-
mental unit of estuarine pollution is the water-
shed. Data for most stressor indicators is not
available for entire watersheds at appropriate
spatial and temporal scales. To interpret environ-
mental relationships, stressor data must be ar-
ranged according to watershed, not according to
regional or political boundaries.
Display of Data on Maps
Although we presented only three maps in the
example assessment report, we attempted to dis-
play various aspects of estuarine condition with
CIS. The actual construction of Estuaria was
accomplished using CIS, and this provided useful
illustrations of political boundaries (Figure 2-5),
land use (Figure 2-6), and the regional distribution
of fish tissue contamination (Figure 2-28).
Effective mapping of EMAP data for estuaries
was not a trivial matter. We found that con-
sistent and broad geographic differences, such as
4-4
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Table 4-2. Estuarine Auxiliary Data Requirements and Sources
Data
Population,
Population Change
Land Use
Flow
River Nutrients and Contami-
nants
NPDES
Atmospheric Deposition
Non-point Nutrient and Contam-
inant Input
Wetlands Loss
Geographic Units
Watershed
Watershed
Major Streams; Watershed
Major Streams; Watershed
Estuary
Watershed; Estuary
Watershed; Estuary
Watershed; Estuary
Sources
U.S. Census Bureau
EMAP Landscape Character-
ization
USGS
USGS, NOAA Status and
Trends
NOAA
EMAP Air and Deposition
NOAA; Dept. of Agriculture;
U.S. Forest Service
U.S. Fish and Wildlife Service
the north-south differences in Estuaria, could be
well-represented. However, the likelihood of this
type of result from any one biogeographic prov-
ince is small.
The representation of regional contamination was
possible because we restricted the occurrence of
subnominal conditions to Region A. However, it
was difficult to portray spatial distributions of
subnominal conditions with respect to other indi-
cators or indices (e.g., benthic community index).
The geographic distribution of estuaries and tidal
rivers presents special problems for EMAP. For
example, illustration of EMAP information for tidal
rivers is difficult: few stations are sampled
within a river, and unless conditions are identical
at all stations, the variations (gradients) in condi-
tion must be presented. This is difficult simply
because the scale of the map is more appropriate
for depiction of regional information. Attempts
to display gradients in tidal rivers result in the
portrayal of condition at individual sites - clearly,
this type of image contradicts the EMAP objec-
tive of representation of regional condition.
Mapping of EMAP information for estuaries is
problematic because estuaries are noncontinuous
resources distributed along the linear boundary of
a coastline. Spatial representation of data works
well for a continuous two-dimensional surface
with an adequate sample density- A well-known
example is land use, where any one map repre-
sentation may consist of thousands of 30 m
pixels. The largest estuary in the United States
is the Chesapeake Bay, in which 24 regular grid
stations were sampled during the EMAP Virginian
Province demonstration project. This sample
density would be sufficient for a contour map of
salinity, but for little else. Each tidal river had
five sample stations, and each small estuary had
a single sample station. It is not yet clear how
EMAP data for discrete resources (such as estu-
aries) will be illustrated on maps. Because
coastlines are linear, information on the three-
dimensional (i.e., latitude, longitude, depth)
aspect of estuarine condition is lost. This
hampers the use of some common CIS tech-
niques such as surface modeling. At best, these
approaches may be attempted, but the presenta-
tion would be fundamentally different from the
surface modeling of two-dimensional landscapes.
Finally, an environmental discontinuity separates
estuaries from their watersheds. Investigation of
associations between measured estuarine indica-
tors and stressors requires some way to relate
the stressor (e.g., poulation density) to either a
specific sampling point or to an estuary. There
are several possible approaches, most of which
require modeling of the estuary and its water-
shed; this would be beyond the scope of EMAP.
We attempted to project atmospheric nitrogen
4-5
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deposition and human population density onto
estuarine sampling stations, but this required a
number of assumptions. For example, we were
not able to model the hydrodynamics of estuar-
ies; therefore, the actual effect of a particular
stressor was not adjusted to reflect the local
hydrologic regime (e.g., flushing rate, tidal
exchange, contribution of surface runoff).
The spatial representation of estuarine condition
requires further thought and research. Broad,
regional differences in condition can be displayed
effectively. However, the scale of maps, the
linear distribution of estuaries, and the disconti-
nuity of resources must be considered in any
attempt to resolve the issue of CIS mapping for
estuarine provinces.
APPLICATIONS OF REALISTIC DATA SETS
We created a realistic data set based on existing
Virginian Province data for development of the
example assessment report. We could have pre-
pared an example assessment report without
using a realistic data set by simply developing a
series of graphics to support reasonable scenarios
for the status and trends of "key" indicators.
The benefits of using a realistic data set justified
the considerable expense of developing and
analyzing the data set.
These benefits included
development of an analysis plan for the
synthesis and integration of data before
data collection is completed;
identification of analytical problems in the
planning phase of the program, while
there is time to solve them;
empirical evaluation of the ability to
detect monotonic trends in data collected
from an EMAP sampling design;
demonstration of the critical importance
of subnominal and marginal thresholds;
demonstration of realistic expectations
for EMAP estuarine data and results.
Details of these benefits are discussed below.
Because EMAP requires timely development of
assessments the analytical approaches must be
well planned and tested prior to actual data
acquisition. We tested several analytical ap-
proaches using the synthetic data and quickly
learned the limitations and benefits associated
with them. We did not exhaust all possibilities,
but we were able to identify at least one ap-
proach that may provide useful information for
assessments. In addition, we can now provide
descriptions of specific analytical problems that
we are likely to encounter; these problems can be
addressed and solved prior to complete acquisi-
tion of data. Actual data for evaluations of
statistically significant trends will not be available
for 10 to 12 years. Because solutions to some
analytical problems may require modifications to
the implementation strategy, it would be disas-
trous to wait until data collection has been
completed to identify and resolve these problems.
A critical finding was that the overall EMAP
sampling design was flexible and supported a
broad variety of analyses. We were able to
demonstrate that monotonic, annual changes of
1 % to 2% in any indicator value (e.g., sediment
concentrations of lead) are detectable using
nonparametric methods. However, we could not
demonstrate that parametric approaches were
useful or appropriate for trend detection. EMAP
will use the model data set developed for this
example assessment in conjunction with the
actual data collected during the 1990 Virginian
Province Demonstration Project to conduct a
detailed evaluation of several aspects of the
sampling design in the future. This detailed
evaluation will include: assessment of sample
allocation schemes, identification of an appropri-
ate spatial scale for representing ecological
condition by estuarine class, and determination of
the likelihood of meeting program objectives (i.e.,
development of data quality objectives).
A realistic data set was not required to dem-
onstrate that EMAP needs to develop environ-
mental condition indices that integrate data for
multiple response indicators. However, a realistic
data set was essential for defining the types of
problems that would be associated with index
development, including composition of indices,
development of weighting factors for variables,
scaling of parameters, and adjustment of indices
for habitat effects (e.g., salinity).
4-6
-------
A realistic data set provided further evidence that
the definition of subnominal and marginal thresh-
olds for indicators and indices is a critical step.
Realistic data were essential to assessing the
sensitivity of analytical results to the thresholds
that were established. Without a realistic data
set, the consequences of misclassifications of
station conditions would not have been apparent.
Undoubtedly, the most important benefit that
resulted from using realistic data is confidence
that the analyses and results are similar to those
that will actually be achieved. This ensures that
we will not build unrealistic expectations for
constituents (i.e., EMAP has not been "over-
sold"). If the example assessment had been
developed from a series of hypothetical graphics,
we would not have had confidence that the final
example would resemble a real assessment
report. An inaccurate example report would
contribute to false expectations and perhaps
mislead EMAP clients.
CONCLUSIONS
Development of an example assessment report
was useful, not only to the investigators involved
in the project, but to the program as a whole.
The production of an example report required a
detailed strategic plan and a clear understanding
of the objectives of EMAP.
The exercise resulted in the following guidelines
for analyzing EMAP data and producing an actual
assessment:
Because of the diverse nature of the
data, the approach for analyzing, inter-
preting, and presenting the data must be
flexible. This is especially important for
long-term programs such as EMAP, in
which program elements may change
over time.
Assessment of condition useful to re-
source management and policy develop-
ment requires a clear definition of nominal
and subnominal conditions and the estab-
lishment of subnominal-marginal thresh-
olds for indicators and indices.
Investigation of associations will require
applicable data for stressor indicators
(e.g., human population density, atmo-
spheric deposition, loadings)
Statistical methods will need to be identi-
fied for investigation of associations be-
tween stressor indicators at regional or
watershed resolution and exposure and
response indicator data at much finer
spatial resolution.
Sufficient time must be allowed for ex-
ploratory statistical analyses and for the
assessment of information. Analytical
investigations of complex and varied data
cannot be constrained by rigid strategies
for data analysis and must be free to
explore the data in ways that may be
dead ends but also may form a new un-
derstanding of the relationship between
natural and anthropogenic stresses and
environmental condition.
Assessment reports communicate information
that culminates years of effort by each resource
group. The production of these reports will
require far more sophisticated analyses and
careful decision-making than data reporting in
annual statistical summaries. As an example of
this difference, we call attention to the experi-
ence of NAPAP (National Acid Precipitation
Assessment Program), which required tremen-
dous effort at the end of the program to produce
an integrated assessment of acidic deposition.
EMAP, with a broader scope than NAPAP, will
require not only greater efforts, but continuous
dedication to this endeavor in order to provide
useful information and insightful assessments of
ecological condition.
4-7
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SECTION 5
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